%%% -*-BibTeX-*- %%% ==================================================================== %%% BibTeX-file{ %%% author = "Nelson H. F. Beebe", %%% version = "1.32", %%% date = "30 April 2024", %%% time = "11:05:50 MST", %%% filename = "tslp.bib", %%% address = "University of Utah %%% Department of Mathematics, 110 LCB %%% 155 S 1400 E RM 233 %%% Salt Lake City, UT 84112-0090 %%% USA", %%% telephone = "+1 801 581 5254", %%% FAX = "+1 801 581 4148", %%% URL = "http://www.math.utah.edu/~beebe", %%% checksum = "03650 3356 17041 162841", %%% email = "beebe at math.utah.edu, beebe at acm.org, %%% beebe at computer.org (Internet)", %%% codetable = "ISO/ASCII", %%% keywords = "ACM Transactions on Speech and Language %%% Processing (TSLP); BibTeX; bibliography", %%% license = "public domain", %%% supported = "yes", %%% docstring = "This is a COMPLETE BibTeX bibliography for %%% ACM Transactions on Speech and Language %%% Processing (TSLP) (CODEN ????, ISSN %%% 1550-4875), covering all journal issues from %%% 2004 -- 2013. %%% %%% In 2014, the journal was merged with IEEE %%% Transactions on Audio, Speech, and Language %%% Processing, and renamed IEEE/ACM Transactions %%% on Audio, Speech, and Language Processing, %%% accessible from IEEE and ACM digital library %%% sites. The new journal is covered in a %%% separate bibliography, ieeeacmtaslp.bib. %%% %%% At version 1.32, the COMPLETE journal %%% coverage looked like this: %%% %%% 2004 ( 1) 2008 ( 3) 2012 ( 8) %%% 2005 ( 5) 2009 ( 2) 2013 ( 23) %%% 2006 ( 7) 2010 ( 3) %%% 2007 ( 12) 2011 ( 21) %%% %%% Article: 85 %%% %%% Total entries: 85 %%% %%% The journal Web pages can be found at: %%% %%% http://www.acm.org/pubs/tslp/ %%% https://dl.acm.org/loi/tslp %%% http://www.signalprocessingsociety.org/publications/periodicals/taslp/ %%% http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6570655 %%% %%% Qualified subscribers can retrieve the full %%% text of recent articles in PDF form. %%% %%% The initial draft was extracted from the ACM %%% Web pages. %%% %%% ACM copyrights explicitly permit abstracting %%% with credit, so article abstracts, keywords, %%% and subject classifications have been %%% included in this bibliography wherever %%% available. Article reviews have been %%% omitted, until their copyright status has %%% been clarified. %%% %%% bibsource keys in the bibliography entries %%% below indicate the entry originally came %%% from the computer science bibliography %%% archive, even though it has likely since %%% been corrected and updated. %%% %%% URL keys in the bibliography point to %%% World Wide Web locations of additional %%% information about the entry. %%% %%% BibTeX citation tags are uniformly chosen %%% as name:year:abbrev, where name is the %%% family name of the first author or editor, %%% year is a 4-digit number, and abbrev is a %%% 3-letter condensation of important title %%% words. Citation tags were automatically %%% generated by software developed for the %%% BibNet Project. %%% %%% In this bibliography, entries are sorted in %%% publication order, using ``bibsort -byvolume.'' %%% %%% The checksum field above contains a CRC-16 %%% checksum as the first value, followed by the %%% equivalent of the standard UNIX wc (word %%% count) utility output of lines, words, and %%% characters. This is produced by Robert %%% Solovay's checksum utility." %%% } %%% ==================================================================== @Preamble{"\input bibnames.sty"} %%% ==================================================================== %%% Acknowledgement abbreviations: @String{ack-nhfb = "Nelson H. F. Beebe, University of Utah, Department of Mathematics, 110 LCB, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090, USA, Tel: +1 801 581 5254, FAX: +1 801 581 4148, e-mail: \path|beebe@math.utah.edu|, \path|beebe@acm.org|, \path|beebe@computer.org| (Internet), URL: \path|http://www.math.utah.edu/~beebe/|"} %%% ==================================================================== %%% Journal abbreviations: @String{j-TSLP = "ACM Transactions on Speech and Language Processing (TSLP)"} %%% ==================================================================== %%% Bibliography entries: @Article{Higashinaka:2004:EDU, author = "Ryuichiro Higashinaka and Noboru Miyazaki and Mikio Nakano and Kiyoaki Aikawa", title = "Evaluating discourse understanding in spoken dialogue systems", journal = j-TSLP, volume = "1", number = "1", pages = "1--20", month = nov, year = "2004", CODEN = "????", DOI = "https://doi.org/10.1145/1035112.1035113", ISSN = "1550-4875", bibdate = "Mon Nov 22 07:30:52 MST 2004", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Verma:2005:VFI, author = "Ashish Verma and Arun Kumar", title = "Voice fonts for individuality representation and transformation", journal = j-TSLP, volume = "2", number = "1", pages = "1--19", month = feb, year = "2005", CODEN = "????", ISSN = "1550-4875", bibdate = "Fri Nov 18 08:15:59 MST 2005", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Koumpis:2005:ASV, author = "Konstantinos Koumpis and Steve Renals", title = "Automatic summarization of voicemail messages using lexical and prosodic features", journal = j-TSLP, volume = "2", number = "1", pages = "1--24", month = feb, year = "2005", CODEN = "????", ISSN = "1550-4875", bibdate = "Fri Nov 18 08:15:59 MST 2005", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Tomko:2005:TEH, author = "Stefanie Tomko and Thomas K. Harris and Arthur Toth and James Sanders and Alexander Rudnicky and Roni Rosenfeld", title = "Towards efficient human machine speech communication: {The} speech graffiti project", journal = j-TSLP, volume = "2", number = "1", pages = "1--27", month = feb, year = "2005", CODEN = "????", ISSN = "1550-4875", bibdate = "Fri Nov 18 08:15:59 MST 2005", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Lapata:2005:WBM, author = "Mirella Lapata and Frank Keller", title = "{Web}-based models for natural language processing", journal = j-TSLP, volume = "2", number = "1", pages = "1--31", month = feb, year = "2005", CODEN = "????", ISSN = "1550-4875", bibdate = "Fri Nov 18 08:15:59 MST 2005", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Federico:2005:WPS, author = "Marcello Federico and Nicola Bertoldi", title = "A word-to-phrase statistical translation model", journal = j-TSLP, volume = "2", number = "2", pages = "1--24", month = dec, year = "2005", CODEN = "????", ISSN = "1550-4875", bibdate = "Thu Feb 16 11:43:49 MST 2006", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Avancini:2006:AED, author = "Henri Avancini and Alberto Lavelli and Fabrizio Sebastiani and Roberto Zanoli", title = "Automatic expansion of domain-specific lexicons by term categorization", journal = j-TSLP, volume = "3", number = "1", pages = "1--30", month = may, year = "2006", CODEN = "????", ISSN = "1550-4875", bibdate = "Wed Jun 14 10:17:29 MDT 2006", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Fung:2006:OSO, author = "Pascale Fung and Grace Ngai", title = "One story, one flow: {Hidden Markov Story Models} for multilingual multidocument summarization", journal = j-TSLP, volume = "3", number = "2", pages = "1--16", month = jul, year = "2006", CODEN = "????", ISSN = "1550-4875", bibdate = "Wed Nov 15 06:40:22 MST 2006", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Wang:2006:HQS, author = "Chao Wang and Stephanie Seneff", title = "High-quality speech-to-speech translation for computer-aided language learning", journal = j-TSLP, volume = "3", number = "2", pages = "1--21", month = jul, year = "2006", CODEN = "????", ISSN = "1550-4875", bibdate = "Wed Nov 15 06:40:22 MST 2006", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Ma:2006:AEC, author = "Ling Ma and Ben Milner and Dan Smith", title = "Acoustic environment classification", journal = j-TSLP, volume = "3", number = "2", pages = "1--22", month = jul, year = "2006", CODEN = "????", ISSN = "1550-4875", bibdate = "Wed Nov 15 06:40:22 MST 2006", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Sporleder:2006:BCP, author = "Caroline Sporleder and Mirella Lapata", title = "Broad coverage paragraph segmentation across languages and domains", journal = j-TSLP, volume = "3", number = "2", pages = "1--35", month = jul, year = "2006", CODEN = "????", ISSN = "1550-4875", bibdate = "Wed Nov 15 06:40:22 MST 2006", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Gandrabur:2006:CEN, author = "Simona Gandrabur and George Foster and Guy Lapalme", title = "Confidence estimation for {NLP} applications", journal = j-TSLP, volume = "3", number = "3", pages = "1--29", month = oct, year = "2006", CODEN = "????", ISSN = "1550-4875", bibdate = "Wed Nov 15 06:39:00 MST 2006", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Hakkani-Tur:2006:AAS, author = "Dilek Hakkani-T{\"u}r and Giuseppe Riccardi and Gokhan Tur", title = "An active approach to spoken language processing", journal = j-TSLP, volume = "3", number = "3", pages = "1--31", month = oct, year = "2006", CODEN = "????", ISSN = "1550-4875", bibdate = "Wed Nov 15 06:39:00 MST 2006", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{VanHalteren:2007:AVL, author = "Hans {Van Halteren}", title = "Author verification by linguistic profiling: {An} exploration of the parameter space", journal = j-TSLP, volume = "4", number = "1", pages = "1:1--1:??", month = jan, year = "2007", CODEN = "????", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:22:59 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This article explores the effects of parameter settings in linguistic profiling, a technique in which large numbers of counts of linguistic features are used as a text profile which can then be compared to average profiles for groups of texts. Although the technique proves to be quite effective for authorship verification, with the best overall parameter settings yielding an equal error rate of 3\% on a test corpus of student essays, the optimal parameters vary greatly depending on author and evaluation criterion.", acknowledgement = ack-nhfb, articleno = "1", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "Authorship attribution; authorship recognition; authorship verification; machine learning", } @Article{Inkpen:2007:SMN, author = "Diana Inkpen", title = "A statistical model for near-synonym choice", journal = j-TSLP, volume = "4", number = "1", pages = "2:1--2:??", month = jan, year = "2007", CODEN = "????", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:22:59 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We present an unsupervised statistical method for automatic choice of near-synonyms when the context is given. The method uses the Web as a corpus to compute scores based on mutual information. Our evaluation experiments show that this method performs better than two previous methods on the same task. We also describe experiments in using supervised learning for this task. We present an application to an intelligent thesaurus. This work is also useful in machine translation and natural language generation.", acknowledgement = ack-nhfb, articleno = "2", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "intelligent thesaurus; Lexical choice; near-synonyms; semantic similarity; Web as a corpus", } @Article{Creutz:2007:UMM, author = "Mathias Creutz and Krista Lagus", title = "Unsupervised models for morpheme segmentation and morphology learning", journal = j-TSLP, volume = "4", number = "1", pages = "3:1--3:??", month = jan, year = "2007", CODEN = "????", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:22:59 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We present a model family called Morfessor for the unsupervised induction of a simple morphology from raw text data. The model is formulated in a probabilistic maximum a posteriori framework. Morfessor can handle highly inflecting and compounding languages where words can consist of lengthy sequences of morphemes. A lexicon of word segments, called morphs, is induced from the data. The lexicon stores information about both the usage and form of the morphs. Several instances of the model are evaluated quantitatively in a morpheme segmentation task on different sized sets of Finnish as well as English data. Morfessor is shown to perform very well compared to a widely known benchmark algorithm, in particular on Finnish data.", acknowledgement = ack-nhfb, articleno = "3", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "Efficient storage; highly inflecting and compounding languages; language independent methods; maximum a posteriori (MAP) estimation; morpheme lexicon and segmentation; unsupervised learning", } @Article{Nenkova:2007:PMI, author = "Ani Nenkova and Rebecca Passonneau and Kathleen McKeown", title = "The {Pyramid Method}: {Incorporating} human content selection variation in summarization evaluation", journal = j-TSLP, volume = "4", number = "2", pages = "4:1--4:??", month = may, year = "2007", CODEN = "????", DOI = "https://doi.org/10.1145/1233912.1233913", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:23:08 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Human variation in content selection in summarization has given rise to some fundamental research questions: How can one incorporate the observed variation in suitable evaluation measures? How can such measures reflect the fact that summaries conveying different content can be equally good and informative? In this article, we address these very questions by proposing a method for analysis of multiple human abstracts into semantic content units. Such analysis allows us not only to quantify human variation in content selection, but also to assign empirical importance weight to different content units. It serves as the basis for an evaluation method, the Pyramid Method, that incorporates the observed variation and is predictive of different equally informative summaries. We discuss the reliability of content unit annotation, the properties of Pyramid scores, and their correlation with other evaluation methods.", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "Evaluation; semantic analysis; summarization", } @Article{Yan:2007:CSD, author = "Jiajun Yan and David B. Bracewell and Shingo Kuroiwa and Fuji Ren", title = "{Chinese} semantic dependency analysis: {Construction} of a treebank and its use in classification", journal = j-TSLP, volume = "4", number = "2", pages = "5:1--5:??", month = may, year = "2007", CODEN = "????", DOI = "https://doi.org/10.1145/1233912.1233914", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:23:08 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Semantic analysis is a standard tool in the Natural Language Processing (NLP) toolbox with widespread applications. In this article, we look at tagging part of the Penn Chinese Treebank with semantic dependency. Then we take this tagged data to train a maximum entropy classifier to label the semantic relations between headwords and dependents to perform semantic analysis on Chinese sentences. The classifier was able to achieve an accuracy of over 84\%. We then analyze the errors in classification to determine the problems and possible solutions for this type of semantic analysis.", acknowledgement = ack-nhfb, articleno = "5", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "Chinese; maximum entropy classification; Natural language processing; semantic dependency analysis", } @Article{Tillmann:2007:BBP, author = "Christoph Tillmann and Tong Zhang", title = "A block bigram prediction model for statistical machine translation", journal = j-TSLP, volume = "4", number = "3", pages = "6:1--6:??", month = jul, year = "2007", CODEN = "????", DOI = "https://doi.org/10.1145/1255171.1255172", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:23:14 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "In this article, we present a novel training method for a localized phrase-based prediction model for statistical machine translation (SMT). The model predicts block neighbors to carry out a phrase-based translation that explicitly handles local phrase reordering. We use a maximum likelihood criterion to train a log-linear block bigram model which uses real-valued features (e.g., a language model score) as well as binary features based on the block identities themselves (e.g., block bigram features). The model training relies on an efficient enumeration of local block neighbors in parallel training data. A novel stochastic gradient descent (SGD) training algorithm is presented that can easily handle millions of features. Moreover, when viewing SMT as a block generation process, it becomes quite similar to sequential natural language annotation problems such as part-of-speech tagging, phrase chunking, or shallow parsing. Our novel approach is successfully tested on a standard Arabic-English translation task using two different phrase reordering models: a block orientation model and a phrase-distortion model.", acknowledgement = ack-nhfb, articleno = "6", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "machine learning; maximum entropy; Statistical machine translation; stochastic gradient descent", } @Article{Hanna:2007:PER, author = "Philip Hanna and Ian O'Neill and Craig Wootton and Michael Mctear", title = "Promoting extension and reuse in a spoken dialog manager: {An} evaluation of the queen's communicator", journal = j-TSLP, volume = "4", number = "3", pages = "7:1--7:??", month = jul, year = "2007", CODEN = "????", DOI = "https://doi.org/10.1145/1255171.1255173", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:23:14 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This article describes how an object-oriented approach can be applied to the architectural design of a spoken language dialog system with the aim of facilitating the modification, extension, and reuse of discourse-related expertise. The architecture of the developed system is described and a functionally similar VoiceXML system is used to provide a comparative baseline across a range of modification and reuse scenarios. It is shown that the use of an object-oriented dialog manager can provide a capable means of reusing existing discourse expertise in a manner that limits the degree of structural decay associated with system change.", acknowledgement = ack-nhfb, articleno = "7", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "dialog management; Human-computer interaction; speech and language processing; spoken dialog systems", } @Article{Higashinaka:2007:UML, author = "Ryuichiro Higashinaka and Marilyn A. Walker and Rashmi Prasad", title = "An unsupervised method for learning generation dictionaries for spoken dialogue systems by mining user reviews", journal = j-TSLP, volume = "4", number = "4", pages = "8:1--8:??", month = oct, year = "2007", CODEN = "????", DOI = "https://doi.org/10.1145/1289600.1289601", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:23:20 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Spoken language generation for dialogue systems requires a dictionary of mappings between the semantic representations of concepts that the system wants to express and the realizations of those concepts. Dictionary creation is a costly process; it is currently done by hand for each dialogue domain. We propose a novel unsupervised method for learning such mappings from user reviews in the target domain and test it in the restaurant and hotel domains. Experimental results show that the acquired mappings achieve high consistency between the semantic representation and the realization and that the naturalness of the realization is significantly higher than the baseline.", acknowledgement = ack-nhfb, articleno = "8", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "generation dictionary; Natural language generation; spoken dialogue systems; user reviews", } @Article{Ringlstetter:2007:ATC, author = "Christoph Ringlstetter and Klaus U. Schulz and Stoyan Mihov", title = "Adaptive text correction with {Web}-crawled domain-dependent dictionaries", journal = j-TSLP, volume = "4", number = "4", pages = "9:1--9:??", month = oct, year = "2007", CODEN = "????", DOI = "https://doi.org/10.1145/1289600.1289602", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:23:20 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "For the success of lexical text correction, high coverage of the underlying background dictionary is crucial. Still, most correction tools are built on top of static dictionaries that represent fixed collections of expressions of a given language. When treating texts from specific domains and areas, often a significant part of the vocabulary is missed. In this situation, both automated and interactive correction systems produce suboptimal results. In this article, we describe strategies for crawling Web pages that fit the thematic domain of the given input text. Special filtering techniques are introduced to avoid pages with many orthographic errors. Collecting the vocabulary of filtered pages that meet the vocabulary of the input text, dynamic dictionaries of modest size are obtained that reach excellent coverage values. A tool has been developed that automatically crawls dictionaries in the indicated way. Our correction experiments with crawled dictionaries, which address English and German document collections from a variety of thematic fields, show that with these dictionaries even the error rate of highly accurate texts can be reduced, using completely automated correction methods. For interactive text correction, more sensible candidate sets for correcting erroneous words are obtained and the manual effort is reduced in a significant way. To complete this picture, we study the effect when using word trigram models for correction. Again, trigram models from crawled corpora outperform those obtained from static corpora.", acknowledgement = ack-nhfb, articleno = "9", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "Adaptive techniques; dictionaries; domains; error correction; Web crawling", } @Article{Bulyko:2007:WRL, author = "Ivan Bulyko and Mari Ostendorf and Manhung Siu and Tim Ng and Andreas Stolcke and {\"O}zg{\"u}r {\c{C}}etin", title = "{Web} resources for language modeling in conversational speech recognition", journal = j-TSLP, volume = "5", number = "1", pages = "1:1--1:25", month = dec, year = "2007", CODEN = "????", DOI = "https://doi.org/10.1145/1322391.1322392", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:23:25 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This article describes a methodology for collecting text from the Web to match a target sublanguage both in style (register) and topic. Unlike other work that estimates n-gram statistics from page counts, the approach here is to select and filter documents, which provides more control over the type of material contributing to the n-gram counts. The data can be used in a variety of ways; here, the different sources are combined in two types of mixture models. Focusing on conversational speech where data collection can be quite costly, experiments demonstrate the positive impact of Web collections on several tasks with varying amounts of data, including Mandarin and English telephone conversations and English meetings and lectures.", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "Conversational speech; language modeling; Web data", } @Article{Giuliano:2007:REI, author = "Claudio Giuliano and Alberto Lavelli and Lorenza Romano", title = "Relation extraction and the influence of automatic named-entity recognition", journal = j-TSLP, volume = "5", number = "1", pages = "2:1--2:26", month = dec, year = "2007", CODEN = "????", DOI = "https://doi.org/10.1145/1322391.1322393", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:23:25 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We present an approach for extracting relations between named entities from natural language documents. The approach is based solely on shallow linguistic processing, such as tokenization, sentence splitting, part-of-speech tagging, and lemmatization. It uses a combination of kernel functions to integrate two different information sources: (i) the whole sentence where the relation appears, and (ii) the local contexts around the interacting entities. We present the results of experiments on extracting five different types of relations from a dataset of newswire documents and show that each information source provides a useful contribution to the recognition task. Usually the combined kernel significantly increases the precision with respect to the basic kernels, sometimes at the cost of a slightly lower recall. Moreover, we performed a set of experiments to assess the influence of the accuracy of named-entity recognition on the performance of the relation-extraction algorithm. Such experiments were performed using both the correct named entities (i.e., those manually annotated in the corpus) and the noisy named entities (i.e., those produced by a machine learning-based named-entity recognizer). The results show that our approach significantly improves the previous results obtained on the same dataset.", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "Information extraction; kernel methods; named-entity recognition; relation extraction", } @Article{Creutz:2007:MBS, author = "Mathias Creutz and Teemu Hirsim{\"a}ki and Mikko Kurimo and Antti Puurula and Janne Pylkk{\"o}nen and Vesa Siivola and Matti Varjokallio and Ebru Arisoy and Murat Sara{\c{c}}lar and Andreas Stolcke", title = "Morph-based speech recognition and modeling of out-of-vocabulary words across languages", journal = j-TSLP, volume = "5", number = "1", pages = "3:1--3:29", month = dec, year = "2007", CODEN = "????", DOI = "https://doi.org/10.1145/1322391.1322394", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:23:25 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We explore the use of morph-based language models in large-vocabulary continuous-speech recognition systems across four so-called morphologically rich languages: Finnish, Estonian, Turkish, and Egyptian Colloquial Arabic. The morphs are subword units discovered in an unsupervised, data-driven way using the Morfessor algorithm. By estimating n -gram language models over sequences of morphs instead of words, the quality of the language model is improved through better vocabulary coverage and reduced data sparsity. Standard word models suffer from high out-of-vocabulary (OOV) rates, whereas the morph models can recognize previously unseen word forms by concatenating morphs. It is shown that the morph models do perform fairly well on OOVs without compromising the recognition accuracy on in-vocabulary words. The Arabic experiment constitutes the only exception since here the standard word model outperforms the morph model. Differences in the datasets and the amount of data are discussed as a plausible explanation.", acknowledgement = ack-nhfb, fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "Egyptian Colloquial Arabic; Estonian; Finnish; Highly inflecting and compounding languages; LVCSR; Morfessor; morpheme; morphologically rich languages; n -gram models; subword-based language modeling; Turkish", } @Article{Zhang:2008:CWS, author = "Ruiqiang Zhang and Keiji Yasuda and Eiichiro Sumita", title = "{Chinese} word segmentation and statistical machine translation", journal = j-TSLP, volume = "5", number = "2", pages = "4:1--4:??", month = may, year = "2008", CODEN = "????", DOI = "https://doi.org/10.1145/1363108.1363109", ISSN = "1550-4875", bibdate = "Mon Jun 16 11:23:34 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Chinese word segmentation (CWS) is a necessary step in Chinese--English statistical machine translation (SMT) and its performance has an impact on the results of SMT. However, there are many choices involved in creating a CWS system such as various specifications and CWS methods. The choices made will create a new CWS scheme, but whether it will produce a superior or inferior translation has remained unknown to date. This article examines the relationship between CWS and SMT. The effects of CWS on SMT were investigated using different specifications and CWS methods. Four specifications were selected for investigation: Beijing University (PKU), Hong Kong City University (CITYU), Microsoft Research (MSR), and Academia SINICA (AS). We created 16 CWS schemes under different settings to examine the relationship between CWS and SMT. Our experimental results showed that the MSR's specifications produced the lowest quality translations. In examining the effects of CWS methods, we tested dictionary-based and CRF-based approaches and found there was no significant difference between the two in the quality of the resulting translations. We also found the correlation between the CWS F-score and SMT BLEU score was very weak. We analyzed CWS errors and their effect on SMT by evaluating systems trained with and without these errors. This article also proposes two methods for combining advantages of different specifications: a simple concatenation of training data and a feature interpolation approach in which the same types of features of translation models from various CWS schemes are linearly interpolated. We found these approaches were very effective in improving the quality of translations.", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "Chinese word segmentation; linear integration; statistical machine translation; translation model", } @Article{Giannakopoulos:2008:SSE, author = "George Giannakopoulos and Vangelis Karkaletsis and George Vouros and Panagiotis Stamatopoulos", title = "Summarization system evaluation revisited: {$N$}-gram graphs", journal = j-TSLP, volume = "5", number = "3", pages = "5:1--5:??", month = oct, year = "2008", CODEN = "????", DOI = "https://doi.org/10.1145/1410358.1410359", ISSN = "1550-4875", bibdate = "Fri Oct 10 13:04:55 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This article presents a novel automatic method (AutoSummENG) for the evaluation of summarization systems, based on comparing the character n-gram graphs representation of the extracted summaries and a number of model summaries. The presented approach is language neutral, due to its statistical nature, and appears to hold a level of evaluation performance that matches and even exceeds other contemporary evaluation methods. Within this study, we measure the effectiveness of different representation methods, namely, word and character n-gram graph and histogram, different n-gram neighborhood indication methods as well as different comparison methods between the supplied representations. A theory for the a priori determination of the methods' parameters along with supporting experiments concludes the study to provide a complete alternative to existing methods concerning the automatic summary system evaluation process.", acknowledgement = ack-nhfb, articleno = "5", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "automatic summarization; n-gram graph; summarization evaluation", } @Article{Shiramatsu:2008:GTM, author = "Shun Shiramatsu and Kazunori Komatani and K{\^o}iti Hasida and Tetsuya Ogata and Hiroshi G. Okuno", title = "A game-theoretic model of referential coherence and its empirical verification using large {Japanese} and {English} corpora", journal = j-TSLP, volume = "5", number = "3", pages = "6:1--6:??", month = oct, year = "2008", CODEN = "????", DOI = "https://doi.org/10.1145/1410358.1410360", ISSN = "1550-4875", bibdate = "Fri Oct 10 13:04:55 MDT 2008", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Referential coherence represents the smoothness of discourse resulting from topic continuity and pronominalization. Rational individuals prefer a referentially coherent structure of discourse when they select a language expression and its interpretation. This is a preference for cooperation in communication. By what principle do they share coherent expressions and interpretations? Centering theory is the standard theory of referential coherence [Grosz et al. 1995]. Although it is well designed on the bases of first-order inference rules [Joshi and Kuhn 1979], it does not embody a behavioral principle for the cooperation evident in communication. Hasida [1996] proposed a game-theoretic hypothesis in relation to this issue. We aim to empirically verify Hasida's hypothesis by using corpora of multiple languages. We statistically design language-dependent parameters by using a corpus of the target language. This statistical design enables us to objectively absorb language-specific differences and to verify the universality of Hasida's hypothesis by using corpora. We empirically verified our model by using large Japanese and English corpora. The result proves the language universality of the hypothesis.", acknowledgement = ack-nhfb, articleno = "6", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "centering theory; corpus statistics; discourse analysis; discourse salience; game theory; game-theoretic pragmatics; meaning game; perceptual utility; pronominalization; reference probability; referential coherence", } @Article{Gliozzo:2009:ITC, author = "Alfio Gliozzo and Carlo Strapparava and Ido Dagan", title = "Improving text categorization bootstrapping via unsupervised learning", journal = j-TSLP, volume = "6", number = "1", pages = "1:1--1:??", month = oct, year = "2009", CODEN = "????", DOI = "https://doi.org/10.1145/1596515.1596516", ISSN = "1550-4875", bibdate = "Fri Oct 9 20:48:21 MDT 2009", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We propose a text-categorization bootstrapping algorithm in which categories are described by relevant seed words. Our method introduces two unsupervised techniques to improve the initial categorization step of the bootstrapping scheme: (i) using latent semantic spaces to estimate the similarity among documents and words, and (ii) the Gaussian mixture algorithm, which differentiates relevant and nonrelevant category information using statistics from unlabeled examples. In particular, this second step maps the similarity scores to class posterior probabilities, and therefore reduces sensitivity to keyword-dependent variations in scores. The algorithm was evaluated on two text categorization tasks, and obtained good performance using only the category names as initial seeds. In particular, the performance of the proposed method proved to be equivalent to a pure supervised approach trained on 70--160 labeled documents per category.", acknowledgement = ack-nhfb, articleno = "1", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "bootstrapping; Text categorization; unsupervised machine learning", } @Article{Murray:2009:ESE, author = "Gabriel Murray and Thomas Kleinbauer and Peter Poller and Tilman Becker and Steve Renals and Jonathan Kilgour", title = "Extrinsic summarization evaluation: {A} decision audit task", journal = j-TSLP, volume = "6", number = "2", pages = "2:1--2:??", month = oct, year = "2009", CODEN = "????", DOI = "https://doi.org/10.1145/1596517.1596518", ISSN = "1550-4875", bibdate = "Fri Oct 9 20:49:17 MDT 2009", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "In this work we describe a large-scale extrinsic evaluation of automatic speech summarization technologies for meeting speech. The particular task is a decision audit, wherein a user must satisfy a complex information need, navigating several meetings in order to gain an understanding of how and why a given decision was made. We compare the usefulness of extractive and abstractive technologies in satisfying this information need, and assess the impact of automatic speech recognition (ASR) errors on user performance. We employ several evaluation methods for participant performance, including post-questionnaire data, human subjective and objective judgments, and a detailed analysis of participant browsing behavior. We find that while ASR errors affect user satisfaction on an information retrieval task, users can adapt their browsing behavior to complete the task satisfactorily. Results also indicate that users consider extractive summaries to be intuitive and useful tools for browsing multimodal meeting data. We discuss areas in which automatic summarization techniques can be improved in comparison with gold-standard meeting abstracts.", acknowledgement = ack-nhfb, articleno = "2", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "abstraction; browsing; evaluation; extraction; interfaces; Summarization", } @Article{Zhu:2010:CBS, author = "Jingbo Zhu and Huizhen Wang and Eduard Hovy and Matthew Ma", title = "Confidence-based stopping criteria for active learning for data annotation", journal = j-TSLP, volume = "6", number = "3", pages = "3:1--3:??", month = apr, year = "2010", CODEN = "????", DOI = "https://doi.org/10.1145/1753783.1753784", ISSN = "1550-4875", bibdate = "Mon Apr 26 14:46:47 MDT 2010", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "The labor-intensive task of labeling data is a serious bottleneck for many supervised learning approaches for natural language processing applications. Active learning aims to reduce the human labeling cost for supervised learning methods. Determining when to stop the active learning process is a very important practical issue in real-world applications. This article addresses the stopping criterion issue of active learning, and presents four simple stopping criteria based on confidence estimation over the unlabeled data pool, including {\em maximum uncertainty}, {\em overall uncertainty}, {\em selected accuracy,\/} and {\em minimum expected error\/} methods. Further, to obtain a proper threshold for a stopping criterion in a specific task, this article presents a strategy by considering the label change factor to dynamically update the predefined threshold of a stopping criterion during the active learning process. To empirically analyze the effectiveness of each stopping criterion for active learning, we design several comparison experiments on seven real-world datasets for three representative natural language processing applications such as word sense disambiguation, text classification and opinion analysis.", acknowledgement = ack-nhfb, articleno = "3", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "active learning; confidence estimation; stopping criterion; text classification; uncertainty sampling; word sense disambiguation", } @Article{Uzeda:2010:CCE, author = "Vin{\'\i}cius Rodrigues Uz{\^e}da and Thiago Alexandre Salgueiro Pardo and Maria Das Gra{\c{c}}as Volpe Nunes", title = "A comprehensive comparative evaluation of {RST}-based summarization methods", journal = j-TSLP, volume = "6", number = "4", pages = "4:1--4:??", month = may, year = "2010", CODEN = "????", DOI = "https://doi.org/10.1145/1767756.1767757", ISSN = "1550-4875", bibdate = "Fri May 14 15:32:31 MDT 2010", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Motivated by governmental, commercial and academic interests, and due to the growing amount of information, mainly online, automatic text summarization area has experienced an increasing number of researches and products, which led to a countless number of summarization methods. In this paper, we present a comprehensive comparative evaluation of the main automatic text summarization methods based on Rhetorical Structure Theory (RST), claimed to be among the best ones. We compare our results to superficial summarizers, which belong to a paradigm with severe limitations, and to hybrid methods, combining RST and superficial methods. We also test voting systems and machine learning techniques trained on RST features. We run experiments for English and Brazilian Portuguese languages and compare the results obtained by using manually and automatically parsed texts. Our results systematically show that all RST methods have comparable overall performance and that they outperform most of the superficial methods. Machine learning techniques achieved high accuracy in the classification of text segments worth of being in the summary, but were not able to produce more informative summaries than the regular RST methods.", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "rhetorical structure theory; text summarization", } @Article{Morin:2010:BBU, author = "Emmanuel Morin and B{\'e}atrice Daille and Koichi Takeuchi and Kyo Kageura", title = "Brains, not brawn: {The} use of ``smart'' comparable corpora in bilingual terminology mining", journal = j-TSLP, volume = "7", number = "1", pages = "1:1--1:??", month = aug, year = "2010", CODEN = "????", DOI = "https://doi.org/10.1145/1839478.1839479", ISSN = "1550-4875", bibdate = "Thu Sep 30 09:11:51 MDT 2010", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Current research in text mining favors the quantity of texts over their representativeness. But for bilingual terminology mining, and for many language pairs, large comparable corpora are not available. More importantly, as terms are defined vis-{\`a}-vis a specific domain with a restricted register, it is expected that the representativeness rather than the quantity of the corpus matters more in terminology mining. Our hypothesis, therefore, is that the representativeness of the corpus is more important than the quantity and ensures the quality of the acquired terminological resources. This article tests this hypothesis on a French--Japanese bilingual term extraction task. To demonstrate how important the type of discourse is as a characteristic of the comparable corpora, we used a state-of-the-art multilingual terminology mining chain composed of two extraction programs, one in each language, and an alignment program. We evaluated the candidate translations using a reference list, and found that taking discourse type into account resulted in candidate translations of a better quality even when the corpus size was reduced by half.", acknowledgement = ack-nhfb, articleno = "1", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", keywords = "comparable corpora; lexical alignment; Terminology mining", } @Article{El-Beltagy:2011:AEL, author = "Samhaa R. El-Beltagy and Ahmed Rafea", title = "An accuracy-enhanced light stemmer for {Arabic} text", journal = j-TSLP, volume = "7", number = "2", pages = "2:1--2:??", month = feb, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1921656.1921657", ISSN = "1550-4875", bibdate = "Tue Feb 22 16:47:19 MST 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Stemming is a key step in most text mining and information retrieval applications. Information extraction, semantic annotation, as well as ontology learning are but a few examples where using a stemmer is a must. While the use of light stemmers in Arabic texts has proven highly effective for the task of information retrieval, this class of stemmers falls short of providing the accuracy required by many text mining applications. This can be attributed to the fact that light stemmers employ a set of rules that they apply indiscriminately and that they do not address stemming of broken plurals at all, even though this class of plurals is very commonly used in Arabic texts.", acknowledgement = ack-nhfb, articleno = "2", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Lemon:2011:ISI, author = "Oliver Lemon and Olivier Pietquin", title = "Introduction to special issue on machine learning for adaptivity in spoken dialogue systems", journal = j-TSLP, volume = "7", number = "3", pages = "3:1--3:??", month = may, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1966407.1966408", ISSN = "1550-4875", bibdate = "Thu Jun 2 07:47:26 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, articleno = "3", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Gavsic:2011:EHD, author = "Milica Gav{\v{s}}i{\'c} and Steve Young", title = "Effective handling of dialogue state in the hidden information state {POMDP}-based dialogue manager", journal = j-TSLP, volume = "7", number = "3", pages = "4:1--4:??", month = may, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1966407.1966409", ISSN = "1550-4875", bibdate = "Thu Jun 2 07:47:26 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Effective dialogue management is critically dependent on the information that is encoded in the dialogue state. In order to deploy reinforcement learning for policy optimization, dialogue must be modeled as a Markov Decision Process. This requires that the dialogue state must encode all relevent information obtained during the dialogue prior to that state. This can be achieved by combining the user goal, the dialogue history, and the last user action to form the dialogue state. In addition, to gain robustness to input errors, dialogue must be modeled as a Partially Observable Markov Decision Process (POMDP) and hence, a distribution over all possible states must be maintained at every dialogue turn.", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Cuayahuitl:2011:SAD, author = "Heriberto Cuay{\'a}huitl and Nina Dethlefs", title = "Spatially-aware dialogue control using hierarchical reinforcement learning", journal = j-TSLP, volume = "7", number = "3", pages = "5:1--5:??", month = may, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1966407.1966410", ISSN = "1550-4875", bibdate = "Thu Jun 2 07:47:26 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This article addresses the problem of scalable optimization for spatially-aware dialogue systems. These kinds of systems must perceive, reason, and act about the spatial environment where they are embedded. We formulate the problem in terms of Semi-Markov Decision Processes and propose a hierarchical reinforcement learning approach to optimize subbehaviors rather than full behaviors. Because of the vast number of policies that are required to control the interaction in a dynamic environment (e.g., a dialogue system assisting a user to navigate in a building from one location to another), our learning approach is based on two stages: (a) the first stage learns low-level behavior, in advance; and (b) the second stage learns high-level behavior, in real time.", acknowledgement = ack-nhfb, articleno = "5", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Jurvcicek:2011:NAB, author = "Filip Jurv{\v{c}}{\'\i}{\v{c}}ek and Blaise Thomson and Steve Young", title = "Natural actor and belief critic: Reinforcement algorithm for learning parameters of dialogue systems modelled as {POMDPs}", journal = j-TSLP, volume = "7", number = "3", pages = "6:1--6:??", month = may, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1966407.1966411", ISSN = "1550-4875", bibdate = "Thu Jun 2 07:47:26 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This article presents a novel algorithm for learning parameters in statistical dialogue systems which are modeled as Partially Observable Markov Decision Processes (POMDPs). The three main components of a POMDP dialogue manager are a dialogue model representing dialogue state information; a policy that selects the system's responses based on the inferred state; and a reward function that specifies the desired behavior of the system. Ideally both the model parameters and the policy would be designed to maximize the cumulative reward. However, while there are many techniques available for learning the optimal policy, no good ways of learning the optimal model parameters that scale to real-world dialogue systems have been found yet.", acknowledgement = ack-nhfb, articleno = "6", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Pietquin:2011:SEB, author = "Olivier Pietquin and Matthieu Geist and Senthilkumar Chandramohan and Herv{\'e} Frezza-Buet", title = "Sample-efficient batch reinforcement learning for dialogue management optimization", journal = j-TSLP, volume = "7", number = "3", pages = "7:1--7:??", month = may, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1966407.1966412", ISSN = "1550-4875", bibdate = "Thu Jun 2 07:47:26 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Spoken Dialogue Systems (SDS) are systems which have the ability to interact with human beings using natural language as the medium of interaction. A dialogue policy plays a crucial role in determining the functioning of the dialogue management module. Handcrafting the dialogue policy is not always an option, considering the complexity of the dialogue task and the stochastic behavior of users. In recent years approaches based on Reinforcement Learning (RL) for policy optimization in dialogue management have been proved to be an efficient approach for dialogue policy optimization. Yet most of the conventional RL algorithms are data intensive and demand techniques such as user simulation.", acknowledgement = ack-nhfb, articleno = "7", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Gonzalez-Brenes:2011:CDH, author = "Jos{\'e} P. Gonz{\'a}lez-Brenes and Jack Mostow", title = "Classifying dialogue in high-dimensional space", journal = j-TSLP, volume = "7", number = "3", pages = "8:1--8:??", month = may, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1966407.1966413", ISSN = "1550-4875", bibdate = "Thu Jun 2 07:47:26 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "The richness of multimodal dialogue makes the space of possible features required to describe it very large relative to the amount of training data. However, conventional classifier learners require large amounts of data to avoid overfitting, or do not generalize well to unseen examples. To learn dialogue classifiers using a rich feature set and fewer data points than features, we apply a recent technique, $\ell_1$-regularized logistic regression. We demonstrate this approach empirically on real data from Project LISTEN's Reading Tutor, which displays a story on a computer screen and listens to a child read aloud. We train a classifier to predict task completion (i.e., whether the student will finish reading the story) with 71\% accuracy on a balanced, unseen test set.", acknowledgement = ack-nhfb, articleno = "8", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Ai:2011:CUS, author = "Hua Ai and Diane Litman", title = "Comparing user simulations for dialogue strategy learning", journal = j-TSLP, volume = "7", number = "3", pages = "9:1--9:??", month = may, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1966407.1966414", ISSN = "1550-4875", bibdate = "Thu Jun 2 07:47:26 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Recent studies show that user simulations can be used to generate training corpora for learning dialogue strategies automatically. However, it is unclear what type of simulation is most suitable in a particular task setting. We observe that a simulation which generates random behaviors in a restricted way outperforms simulations that mimic human user behaviors in a statistical way. Our finding suggests that we do not always need to construct a realistic user simulation. Since constructing realistic user simulations is not a trivial task, we can save engineering cost by wisely choosing simulation models that are appropriate for our task.", acknowledgement = ack-nhfb, articleno = "9", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Misu:2011:MSD, author = "Teruhisa Misu and Komei Sugiura and Tatsuya Kawahara and Kiyonori Ohtake and Chiori Hori and Hideki Kashioka and Hisashi Kawai and Satoshi Nakamura", title = "Modeling spoken decision support dialogue and optimization of its dialogue strategy", journal = j-TSLP, volume = "7", number = "3", pages = "10:1--10:??", month = may, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1966407.1966415", ISSN = "1550-4875", bibdate = "Thu Jun 2 07:47:26 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This article presents a user model for user simulation and a system state representation in spoken decision support dialogue systems. When selecting from a group of alternatives, users apply different decision-making criteria with different priorities. At the beginning of the dialogue, however, users often do not have a definite goal or criteria in which they place value, thus they can learn about new features while interacting with the system and accordingly create new criteria. In this article, we present a user model and dialogue state representation that accommodate these patterns by considering the user's knowledge and preferences. To estimate the parameters used in the user model, we implemented a trial sightseeing guidance system, collected dialogue data, and trained a user simulator.", acknowledgement = ack-nhfb, articleno = "10", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Potamianos:2011:ISI, author = "Alexandros Potamianos and Diego Giuliani and Shrikanth S. Narayanan and Kay Berkling", title = "Introduction to the special issue on speech and language processing of children's speech for child-machine interaction applications", journal = j-TSLP, volume = "7", number = "4", pages = "11:1--11:??", month = aug, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1998384.1998385", ISSN = "1550-4875", bibdate = "Wed Aug 17 09:52:06 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, articleno = "11", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Wollmer:2011:TDC, author = "Martin W{\"o}llmer and Bj{\"o}rn Schuller and Anton Batliner and Stefan Steidl and Dino Seppi", title = "Tandem decoding of children's speech for keyword detection in a child-robot interaction scenario", journal = j-TSLP, volume = "7", number = "4", pages = "12:1--12:??", month = aug, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1998384.1998386", ISSN = "1550-4875", bibdate = "Wed Aug 17 09:52:06 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "In this article, we focus on keyword detection in children's speech as it is needed in voice command systems. We use the FAU Aibo Emotion Corpus which contains emotionally colored spontaneous children's speech recorded in a child-robot interaction scenario and investigate various recent keyword spotting techniques. As the principle of bidirectional Long Short-Term Memory (BLSTM) is known to be well-suited for context-sensitive phoneme prediction, we incorporate a BLSTM network into a Tandem model for flexible coarticulation modeling in children's speech. Our experiments reveal that the Tandem model prevails over a triphone-based Hidden Markov Model approach.", acknowledgement = ack-nhfb, articleno = "12", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Meinedo:2011:AGD, author = "Hugo Meinedo and Isabel Trancoso", title = "Age and gender detection in the {I-DASH} project", journal = j-TSLP, volume = "7", number = "4", pages = "13:1--13:??", month = aug, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1998384.1998387", ISSN = "1550-4875", bibdate = "Wed Aug 17 09:52:06 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This article presents a description of the INESC-ID Age and Gender classification systems which were developed for aiding the detection of child abuse material within the scope of the European project I-DASH. The Age and Gender classification systems are composed respectively by the fusion of four and six individual subsystems trained with short- and long-term acoustic and prosodic features, different classification strategies, Gaussian Mixture Models-Universal Background Model (GMM-UBM), Multi-Layer Perceptrons (MLP) and Support Vector Machines (SVM), trained over five different speech corpus. The best results obtained by the calibration and linear logistic regression fusion back-end show an absolute improvement of 2\% on the unweighted accuracy value for the Age and 1\% for the Gender when compared to the best individual frontend systems in the development set.", acknowledgement = ack-nhfb, articleno = "13", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Duong:2011:TMA, author = "Minh Duong and Jack Mostow and Sunayana Sitaram", title = "Two methods for assessing oral reading prosody", journal = j-TSLP, volume = "7", number = "4", pages = "14:1--14:??", month = aug, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1998384.1998388", ISSN = "1550-4875", bibdate = "Wed Aug 17 09:52:06 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We compare two types of models to assess the prosody of children's oral reading. Template models measure how well the child's prosodic contour in reading a given sentence correlates in pitch, intensity, pauses, or word reading times with an adult narration of the same sentence. We evaluate template models directly against a common rubric used to assess fluency by hand, and indirectly by their ability to predict fluency and comprehension test scores and gains of 10 children who used Project LISTEN's Reading Tutor; the template models outpredict the human assessment. We also use the same set of adult narrations to train generalized models for mapping text to prosody, and use them to evaluate children's prosody.", acknowledgement = ack-nhfb, articleno = "14", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Black:2011:AAA, author = "Matthew P. Black and Abe Kazemzadeh and Joseph Tepperman and Shrikanth S. Narayanan", title = "Automatically assessing the {ABCs}: Verification of children's spoken letter-names and letter-sounds", journal = j-TSLP, volume = "7", number = "4", pages = "15:1--15:??", month = aug, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1998384.1998389", ISSN = "1550-4875", bibdate = "Wed Aug 17 09:52:06 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Automatic literacy assessment is an area of research that has shown significant progress in recent years. Technology can be used to automatically administer reading tasks and analyze and interpret children's reading skills. It has the potential to transform the classroom dynamic by providing useful information to teachers in a repeatable, consistent, and affordable way. While most previous research has focused on automatically assessing children reading words and sentences, assessments of children's earlier foundational skills is needed. We address this problem in this research by automatically verifying preliterate children's pronunciations of English letter-names and the sounds each letter represents (``letter-sounds''). The children analyzed in this study were from a diverse bilingual background and were recorded in actual kindergarten to second grade classrooms.", acknowledgement = ack-nhfb, articleno = "15", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Bolanos:2011:FFO, author = "Daniel Bola{\~n}os and Ronald A. Cole and Wayne Ward and Eric Borts and Edward Svirsky", title = "{FLORA}: Fluent oral reading assessment of children's speech", journal = j-TSLP, volume = "7", number = "4", pages = "16:1--16:??", month = aug, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1998384.1998390", ISSN = "1550-4875", bibdate = "Wed Aug 17 09:52:06 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We present initial results of FLORA, an accessible computer program that uses speech recognition to provide an accurate measure of children's oral reading ability. FLORA presents grade-level text passages to children, who read the passages out loud, and computes the number of words correct per minute (WCPM), a standard measure of oral reading fluency. We describe the main components of the FLORA program, including the system architecture and the speech recognition subsystems. We compare results of FLORA to human scoring on 783 recordings of grade level text passages read aloud by first through fourth grade students in classroom settings.", acknowledgement = ack-nhfb, articleno = "16", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Maier:2011:AVR, author = "Andreas Maier and Flonan H{\"o}nig and Stefan Steidl and Elmar N{\"o}th and Stefanie Horndasch and Elisabeth Sauerh{\"o}fer and Oliver Kratz and Gunther Moll", title = "An automatic version of a reading disorder test", journal = j-TSLP, volume = "7", number = "4", pages = "17:1--17:??", month = aug, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1998384.1998391", ISSN = "1550-4875", bibdate = "Wed Aug 17 09:52:06 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We present a novel system to automatically diagnose reading disorders. The system is based on a speech recognition engine with a module for prosodic analysis. The reading disorder test is based on eight different subtests. In each of the subtests, the system achieves a recognition accuracy of at least 95\%. As in the perceptual version of the test, the results of the subtests are then joined into a final test result to determine whether the child has a reading disorder. In the final classification stage, the system identifies 98.3\% of the 120 children correctly.", acknowledgement = ack-nhfb, articleno = "17", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Ward:2011:MST, author = "Wayne Ward and Ronald Cole and Daniel Bola{\~n}os and Cindy Buchenroth-Martin and Edward Svirsky and Sarel {Van Vuuren} and Timothy Weston and Jing Zheng and Lee Becker", title = "My science tutor: {A} conversational multimedia virtual tutor for elementary school science", journal = j-TSLP, volume = "7", number = "4", pages = "18:1--18:??", month = aug, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/1998384.1998392", ISSN = "1550-4875", bibdate = "Wed Aug 17 09:52:06 MDT 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This article describes My Science Tutor (MyST), an intelligent tutoring system designed to improve science learning by students in 3rd, 4th, and 5th grades (7 to 11 years old) through conversational dialogs with a virtual science tutor. In our study, individual students engage in spoken dialogs with the virtual tutor Marni during 15 to 20 minute sessions following classroom science investigations to discuss and extend concepts embedded in the investigations. The spoken dialogs in MyST are designed to scaffold learning by presenting open-ended questions accompanied by illustrations or animations related to the classroom investigations and the science concepts being learned. The focus of the interactions is to elicit self-expression from students.", acknowledgement = ack-nhfb, articleno = "18", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Turunen:2011:SRU, author = "Ville T. Turunen and Mikko Kurimo", title = "Speech retrieval from unsegmented {Finnish} audio using statistical morpheme-like units for segmentation, recognition, and retrieval", journal = j-TSLP, volume = "8", number = "1", pages = "1:1--1:??", month = oct, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/2036916.2036917", ISSN = "1550-4875", bibdate = "Thu Dec 15 08:44:09 MST 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, articleno = "1", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Hassan:2011:LIE, author = "Samer Hassan and Rada Mihalcea", title = "Learning to identify educational materials", journal = j-TSLP, volume = "8", number = "2", pages = "2:1--2:??", month = nov, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/2050100.2050101", ISSN = "1550-4875", bibdate = "Thu Dec 15 08:44:09 MST 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, articleno = "2", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Peirsman:2011:SRB, author = "Yves Peirsman and Sebastian Pad{\'o}", title = "Semantic relations in bilingual lexicons", journal = j-TSLP, volume = "8", number = "2", pages = "3:1--3:??", month = nov, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/2050100.2050102", ISSN = "1550-4875", bibdate = "Thu Dec 15 08:44:09 MST 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, articleno = "3", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Kordjamshidi:2011:SRL, author = "Parisa Kordjamshidi and Martijn {Van Otterlo} and Marie-Francine Moens", title = "Spatial role labeling: {Towards} extraction of spatial relations from natural language", journal = j-TSLP, volume = "8", number = "3", pages = "4:1--4:??", month = dec, year = "2011", CODEN = "????", DOI = "https://doi.org/10.1145/2050104.2050105", ISSN = "1550-4875", bibdate = "Thu Dec 15 08:44:09 MST 2011", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This article reports on the novel task of spatial role labeling in natural language text. It proposes machine learning methods to extract spatial roles and their relations. This work experiments with both a step-wise approach, where spatial prepositions are found and the related trajectors, and landmarks are then extracted, and a joint learning approach, where a spatial relation and its composing indicator, trajector, and landmark are classified collectively. Context-dependent learning techniques, such as a skip-chain conditional random field, yield good results on the GUM-evaluation (Maptask) data and CLEF-IAPR TC-12 Image Benchmark.", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Zhu:2012:UBA, author = "Jingbo Zhu and Matthew Ma", title = "Uncertainty-based active learning with instability estimation for text classification", journal = j-TSLP, volume = "8", number = "4", pages = "5:1--5:??", month = feb, year = "2012", CODEN = "????", DOI = "https://doi.org/10.1145/2093153.2093154", ISSN = "1550-4875", bibdate = "Wed Feb 15 18:13:35 MST 2012", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This article deals with pool-based active learning with uncertainty sampling. While existing uncertainty sampling methods emphasize selection of instances near the decision boundary to increase the likelihood of selecting informative examples, our position is that this heuristic is a surrogate for selecting examples for which the current learning algorithm iteration is likely to misclassify. To more directly model this intuition, this article augments such uncertainty sampling methods and proposes a simple instability-based selective sampling approach to improving uncertainty-based active learning, in which the instability degree of each unlabeled example is estimated during the learning process. Experiments on seven evaluation datasets show that instability-based sampling methods can achieve significant improvements over the traditional uncertainty sampling method.", acknowledgement = ack-nhfb, articleno = "5", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Zhang:2012:ALS, author = "Justin Jian Zhang and Pascale Fung", title = "Active learning with semi-automatic annotation for extractive speech summarization", journal = j-TSLP, volume = "8", number = "4", pages = "6:1--6:??", month = feb, year = "2012", CODEN = "????", DOI = "https://doi.org/10.1145/2093153.2093155", ISSN = "1550-4875", bibdate = "Wed Feb 15 18:13:35 MST 2012", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We propose using active learning for extractive speech summarization in order to reduce human effort in generating reference summaries. Active learning chooses a selective set of samples to be labeled. We propose a combination of informativeness and representativeness criteria for selection. We further propose a semi-automatic method to generate reference summaries for presentation speech by using Relaxed Dynamic Time Warping (RDTW) alignment between presentation speech and its accompanied slides. Our summarization results show that the amount of labeled data needed for a given summarization accuracy can be reduced by more than 23\% compared to random sampling.", acknowledgement = ack-nhfb, articleno = "6", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Raux:2012:OTT, author = "Antoine Raux and Maxine Eskenazi", title = "Optimizing the turn-taking behavior of task-oriented spoken dialog systems", journal = j-TSLP, volume = "9", number = "1", pages = "1:1--1:??", month = may, year = "2012", CODEN = "????", DOI = "https://doi.org/10.1145/2168748.2168749", ISSN = "1550-4875", bibdate = "Tue May 15 16:57:47 MDT 2012", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Even as progress in speech technologies and task and dialog modeling has allowed the development of advanced spoken dialog systems, the low-level interaction behavior of those systems often remains rigid and inefficient. Based on an analysis of human-human and human-computer turn-taking in naturally occurring task-oriented dialogs, we define a set of features that can be automatically extracted and show that they can be used to inform efficient end-of-turn detection. We then frame turn-taking as decision making under uncertainty and describe the Finite-State Turn-Taking Machine (FSTTM), a decision-theoretic model that combines data-driven machine learning methods and a cost structure derived from Conversation Analysis to control the turn-taking behavior of dialog systems. Evaluation results on CMU Let's Go, a publicly deployed bus information system, confirm that the FSTTM significantly improves the responsiveness of the system compared to a standard threshold-based approach, as well as previous data-driven methods.", acknowledgement = ack-nhfb, articleno = "1", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Abdalgader:2012:USB, author = "Khaled Abdalgader and Andrew Skabar", title = "Unsupervised similarity-based word sense disambiguation using context vectors and sentential word importance", journal = j-TSLP, volume = "9", number = "1", pages = "2:1--2:??", month = may, year = "2012", CODEN = "????", DOI = "https://doi.org/10.1145/2168748.2168750", ISSN = "1550-4875", bibdate = "Tue May 15 16:57:47 MDT 2012", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "The process of identifying the actual meanings of words in a given text fragment has a long history in the field of computational linguistics. Due to its importance in understanding the semantics of natural language, it is considered one of the most challenging problems facing this field. In this article we propose a new unsupervised similarity-based word sense disambiguation (WSD) algorithm that operates by computing the semantic similarity between glosses of the target word and a context vector. The sense of the target word is determined as that for which the similarity between gloss and context vector is greatest. Thus, whereas conventional unsupervised WSD methods are based on measuring pairwise similarity between words, our approach is based on measuring semantic similarity between sentences. This enables it to utilize a higher degree of semantic information, and is more consistent with the way that human beings disambiguate; that is, by considering the greater context in which the word appears. We also show how performance can be further improved by incorporating a preliminary step in which the relative importance of words within the original text fragment is estimated, thereby providing an ordering that can be used to determine the sequence in which words should be disambiguated. We provide empirical results that show that our method performs favorably against the state-of-the-art unsupervised word sense disambiguation methods, as evaluated on several benchmark datasets through different models of evaluation.", acknowledgement = ack-nhfb, articleno = "2", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Bouayad-Agha:2012:POG, author = "Nadjet Bouayad-Agha and Gerard Casamayor and Simon Mille and Leo Wanner", title = "Perspective-oriented generation of football match summaries: old tasks, new challenges", journal = j-TSLP, volume = "9", number = "2", pages = "3:1--3:??", month = jul, year = "2012", CODEN = "????", DOI = "https://doi.org/10.1145/2287710.2287711", ISSN = "1550-4875", bibdate = "Tue Jul 31 17:49:24 MDT 2012", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Team sports commentaries call for techniques that are able to select content and generate wordings to reflect the affinity of the targeted reader for one of the teams. The existing works tend to have in common that they either start from knowledge sources of limited size to whose structures then different ways of realization are explicitly assigned, or they work directly with linguistic corpora, without the use of a deep knowledge source. With the increasing availability of large-scale ontologies this is no longer satisfactory: techniques are needed that are applicable to general purpose ontologies, but which still take user preferences into account. We take the best of both worlds in that we use a two-layer ontology. The first layer is composed of raw domain data modelled in an application-independent base OWL ontology. The second layer contains a rich perspective generation-motivated domain communication knowledge ontology, inferred from the base ontology. The two-layer ontology allows us to take into account user perspective-oriented criteria at different stages of generation to generate perspective-oriented commentaries. We show how content selection, discourse structuring, information structure determination, and lexicalization are driven by these criteria and how stage after stage a truly user perspective-tailored summary is generated. The viability of our proposal has been evaluated for the generation of football match summaries of the First Spanish Football League. The reported outcome of the evaluation demonstrates that we are on the right track.", acknowledgement = ack-nhfb, articleno = "3", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Sakti:2012:DST, author = "Sakriani Sakti and Michael Paul and Andrew Finch and Xinhui Hu and Jinfu Ni and Noriyuki Kimura and Shigeki Matsuda and Chiori Hori and Yutaka Ashikari and Hisashi Kawai and Hideki Kashioka and Eiichiro Sumita and Satoshi Nakamura", title = "Distributed speech translation technologies for multiparty multilingual communication", journal = j-TSLP, volume = "9", number = "2", pages = "4:1--4:??", month = jul, year = "2012", CODEN = "????", DOI = "https://doi.org/10.1145/2287710.2287712", ISSN = "1550-4875", bibdate = "Tue Jul 31 17:49:24 MDT 2012", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Developing a multilingual speech translation system requires efforts in constructing automatic speech recognition (ASR), machine translation (MT), and text-to-speech synthesis (TTS) components for all possible source and target languages. If the numerous ASR, MT, and TTS systems for different language pairs developed independently in different parts of the world could be connected, multilingual speech translation systems for a multitude of language pairs could be achieved. Yet, there is currently no common, flexible framework that can provide an entire speech translation process by bringing together heterogeneous speech translation components. In this article we therefore propose a distributed architecture framework for multilingual speech translation in which all speech translation components are provided on distributed servers and cooperate over a network. This framework can facilitate the connection of different components and functions. To show the overall mechanism, we first present our state-of-the-art technologies for multilingual ASR, MT, and TTS components, and then describe how to combine those systems into the proposed network-based framework. The client applications are implemented on a handheld mobile terminal device, and all data exchanges among client users and spoken language technology servers are managed through a Web protocol. To support multiparty communication, an additional communication server is provided for simultaneously distributing the speech translation results from one user to multiple users. Field testing shows that the system is capable of realizing multiparty multilingual speech translation for real-time and location-independent communication.", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Narendra:2012:SSU, author = "N. P. Narendra and K. Sreenivasa Rao", title = "Syllable Specific Unit Selection Cost Functions for Text-to-Speech Synthesis", journal = j-TSLP, volume = "9", number = "3", pages = "5:1--5:??", month = nov, year = "2012", CODEN = "????", DOI = "https://doi.org/10.1145/2382434.2382435", ISSN = "1550-4875", bibdate = "Tue Nov 20 18:42:07 MST 2012", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This paper presents the design and development of syllable specific unit selection cost functions for improving the quality of text-to-speech synthesis. Appropriate unit selection cost functions, namely concatenation cost and target cost, are proposed for syllable based synthesis. Concatenation costs are defined based on the type of segments present at the syllable joins. Proposed concatenation costs have shown significant reduction in perceptual discontinuity at syllable joins. Three-stage target cost formulation is proposed for selecting appropriate units from database. Subjective evaluation has shown improvement in the quality of speech at each stage.", acknowledgement = ack-nhfb, articleno = "5", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Rentoumi:2012:IML, author = "Vassiliki Rentoumi and George A. Vouros and Vangelis Karkaletsis and Amalia Moser", title = "Investigating Metaphorical Language in Sentiment Analysis: a Sense-to-Sentiment Perspective", journal = j-TSLP, volume = "9", number = "3", pages = "6:1--6:??", month = nov, year = "2012", CODEN = "????", DOI = "https://doi.org/10.1145/2382434.2382436", ISSN = "1550-4875", bibdate = "Tue Nov 20 18:42:07 MST 2012", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Intuition dictates that figurative language and especially metaphorical expressions should convey sentiment. It is the aim of this work to validate this intuition by showing that figurative language (metaphors) appearing in a sentence drive the polarity of that sentence. Towards this target, the current article proposes an approach for sentiment analysis of sentences where figurative language plays a dominant role. This approach applies Word Sense Disambiguation aiming to assign polarity to word senses rather than tokens. Sentence polarity is determined using the individual polarities for metaphorical senses as well as other contextual information. Experimental evaluation shows that the proposed method achieves high scores in comparison with other state-of-the-art approaches tested on the same corpora. Finally, experimental results provide supportive evidence that this method is also well suited for corpora consisting of literal and figurative language sentences.", acknowledgement = ack-nhfb, articleno = "6", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Corazza:2013:ITM, author = "Anna Corazza and Alberto Lavelli and Giorgio Satta", title = "An information-theoretic measure to evaluate parsing difficulty across treebanks", journal = j-TSLP, volume = "9", number = "4", pages = "7:1--7:??", month = jan, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2407736.2407737", ISSN = "1550-4875", bibdate = "Wed Mar 20 06:19:16 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "With the growing interest in statistical parsing, special attention has recently been devoted to the problem of comparing different treebanks to assess which languages or domains are more difficult to parse relative to a given model. A common methodology for comparing parsing difficulty across treebanks is based on the use of the standard labeled precision and recall measures. As an alternative, in this article we propose an information-theoretic measure, called the expected conditional cross-entropy (ECC). One important advantage with respect to standard performance measures is that ECC can be directly expressed as a function of the parameters of the model. We evaluate ECC across several treebanks for English, French, German, and Italian, and show that ECC is an effective measure of parsing difficulty, with an increase in ECC always accompanied by a degradation in parsing accuracy.", acknowledgement = ack-nhfb, articleno = "7", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Zhang:2013:CAL, author = "Li Zhang", title = "Contextual and active learning-based affect-sensing from virtual drama improvisation", journal = j-TSLP, volume = "9", number = "4", pages = "8:1--8:??", month = jan, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2407736.2407738", ISSN = "1550-4875", bibdate = "Wed Mar 20 06:19:16 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Affect interpretation from open-ended drama improvisation is a challenging task. This article describes experiments in using latent semantic analysis to identify discussion themes and potential target audiences for those improvisational inputs without strong affect indicators. A context-based affect-detection is also implemented using a supervised neural network with the consideration of emotional contexts of most intended audiences, sentence types, and interpersonal relationships. In order to go beyond the constraints of predefined scenarios and improve the system's robustness, min-margin-based active learning is implemented. This active learning algorithm also shows great potential in dealing with imbalanced affect classifications. Evaluation results indicated that the context-based affect detection achieved an averaged precision of 0.826 and an averaged recall of 0.813 for affect detection of the test inputs from the Crohn's disease scenario using three emotion labels: positive, negative, and neutral, and an averaged precision of 0.868 and an average recall of 0.876 for the test inputs from the school bullying scenario. Moreover, experimental evaluation on a benchmark data set for active learning demonstrated that active learning was able to greatly reduce human annotation efforts for the training of affect detection, and also showed promising robustness in dealing with open-ended example inputs beyond the improvisation of the chosen scenarios.", acknowledgement = ack-nhfb, articleno = "8", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Duh:2013:MID, author = "Kevin Duh and Ching-Man Au Yeung and Tomoharu Iwata and Masaaki Nagata", title = "Managing information disparity in multilingual document collections", journal = j-TSLP, volume = "10", number = "1", pages = "1:1--1:??", month = mar, year = "2013", CODEN = "????", ISSN = "1550-4875", bibdate = "Wed Mar 20 06:19:18 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Information disparity is a major challenge with multilingual document collections. When documents are dynamically updated in a distributed fashion, information content among different language editions may gradually diverge. We propose a framework for assisting human editors to manage this information disparity, using tools from machine translation and machine learning. Given source and target documents in two different languages, our system automatically identifies information nuggets that are new with respect to the target and suggests positions to place their translations. We perform both real-world experiments and large-scale simulations on Wikipedia documents and conclude our system is effective in a variety of scenarios.", acknowledgement = ack-nhfb, articleno = "1", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Zhang:2013:TCL, author = "Renxian Zhang and Wenjie Li and Dehong Gao", title = "Towards content-level coherence with aspect-guided summarization", journal = j-TSLP, volume = "10", number = "1", pages = "2:1--2:??", month = mar, year = "2013", CODEN = "????", ISSN = "1550-4875", bibdate = "Wed Mar 20 06:19:18 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "The TAC 2010 summarization track initiated a new task-aspect-guided summarization-that centers on textual aspects embodied as particular kinds of information of a text. We observe that aspect-guided summaries not only address highly specific user need, but also facilitate content-level coherence by using aspect information. In this article, we present a full-fledged approach to aspect-guided summarization with a focus on summary coherence. Our summarization approach depends on two prerequisite subtasks: recognizing aspect-bearing sentences in order to do sentence extraction, and modeling aspect-based coherence with an HMM model in order to predict a coherent sentence ordering. Using the manually annotated TAC 2010 and 2010 datasets, we validated the effectiveness of our proposed methods for those subtasks. Drawing on the empirical results, we proceed to develop an aspect-guided summarizer based on a simple but robust base summarizer. With sentence selection guided by aspect information, our system is one of the best on TAC 2011. With sentence ordering predicted by the aspect-based HMM model, the summaries achieve good coherence.", acknowledgement = ack-nhfb, articleno = "2", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Ramisch:2013:ISI, author = "Carlos Ramisch and Aline Villavicencio and Valia Kordoni", title = "Introduction to the special issue on multiword expressions: From theory to practice and use", journal = j-TSLP, volume = "10", number = "2", pages = "3:1--3:??", month = jun, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2483691.2483692", ISSN = "1550-4875", bibdate = "Mon Jul 1 18:16:29 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We are in 2013, and multiword expressions have been around for a while in the computational linguistics research community. Since the first ACL workshop on MWEs 12 years ago in Sapporo, Japan, much has been discussed, proposed, experimented, evaluated and argued about MWEs. And yet, they deserve the publication of a whole special issue of the ACM Transactions on Speech and Language Processing. But what is it about multiword expressions that keeps them in fashion? Who are the people and the institutions who perform and publish groundbreaking fundamental and applied research in this field? What is the place and the relevance of our lively research community in the bigger picture of computational linguistics? Where do we come from as a community, and most importantly, where are we heading? In this introductory article, we share our point of view about the answers to these questions and introduce the articles that compose the current special issue.", acknowledgement = ack-nhfb, articleno = "3", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Church:2013:HMM, author = "Kenneth Church", title = "How many multiword expressions do people know?", journal = j-TSLP, volume = "10", number = "2", pages = "4:1--4:??", month = jun, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2483691.2483693", ISSN = "1550-4875", bibdate = "Mon Jul 1 18:16:29 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "What is a multiword expression (MWE) and how many are there? Mark Liberman gave a great invited talk at ACL-89, titled ``How Many Words Do People Know?'' where he spent the entire hour questioning the question. Many of the same questions apply to multiword expressions. What is a word? An expression? What is many? What is a person? What does it mean to know? Rather than answer these questions, this article will use them as Liberman did, as an excuse for surveying how such issues are addressed in a variety of fields: computer science, Web search, linguistics, lexicography, educational testing, psychology, statistics, and so on.", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Davis:2013:LSF, author = "Anthony R. Davis and Leslie Barrett", title = "Lexical semantic factors in the acceptability of {English} support-verb-nominalization constructions", journal = j-TSLP, volume = "10", number = "2", pages = "5:1--5:??", month = jun, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2483691.2483694", ISSN = "1550-4875", bibdate = "Mon Jul 1 18:16:29 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We explore the properties of support-verb and nominalization (SVN) pairs in English, a type of multiword expression in which a semantically impoverished verb combines with a complement nominalization sharing an unexpressed role with the verb. This study follows others in seeking syntactic or lexical semantic factors correlated with the acceptability of these constructions. In particular, following recent work showing certain semantic verb class features to improve SVN classification [Tu and Roth 2011], we explore the possibility that support verbs and the verbal roots of nominalizations in acceptable SVN pairs are clustered according to the classes of Levin [1993]. We compare the compatibility correlation of these results with those of the Aktionsart-class-based proposal of Barrett and Davis [2002]. We find the evidence that Levin classes are a factor in the acceptability of SVN constructions to be equivocal, and conclude with a discussion of the reasons for this finding.", acknowledgement = ack-nhfb, articleno = "5", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Vincze:2013:LDE, author = "Veronika Vincze and Istv{\'a}n Nagy T. and J{\'a}nos Zsibrita", title = "Learning to detect {English} and {Hungarian} light verb constructions", journal = j-TSLP, volume = "10", number = "2", pages = "6:1--6:??", month = jun, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2483691.2483695", ISSN = "1550-4875", bibdate = "Mon Jul 1 18:16:29 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Light verb constructions consist of a verbal and a nominal component, where the noun preserves its original meaning while the verb has lost it (to some degree). They are syntactically flexible and their meaning can only be partially computed on the basis of the meaning of their parts, thus they require special treatment in natural language processing. For this purpose, the first step is to identify light verb constructions. In this study, we present our conditional random fields-based tool-called FXTagger-for identifying light verb constructions. The flexibility of the tool is demonstrated on two, typologically different, languages, namely, English and Hungarian. As earlier studies labeled different linguistic phenomena as light verb constructions, we first present a linguistics-based classification of light verb constructions and then show that FXTagger is able to identify different classes of light verb constructions in both languages. Different types of texts may contain different types of light verb constructions; moreover, the frequency of light verb constructions may differ from domain to domain. Hence we focus on the portability of models trained on different corpora, and we also investigate the effect of simple domain adaptation techniques to reduce the gap between the domains. Our results show that in spite of domain specificities, out-domain data can also contribute to the successful LVC detection in all domains.", acknowledgement = ack-nhfb, articleno = "6", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Nissim:2013:MIV, author = "Malvina Nissim and Andrea Zaninello", title = "Modeling the internal variability of multiword expressions through a pattern-based method", journal = j-TSLP, volume = "10", number = "2", pages = "7:1--7:??", month = jun, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2483691.2483696", ISSN = "1550-4875", bibdate = "Mon Jul 1 18:16:29 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "The issue of internal variability of multiword expressions (MWEs) is crucial towards their identification and extraction in running text. We present a corpus-supported and computational study on Italian MWEs, aimed at defining an automatic method for modeling internal variation, exploiting frequency and part-of-speech (POS) information. We do so by deriving an XML-encoded lexicon of MWEs based on a manually compiled dictionary, which is then projected onto a a large corpus. Since a search for fixed forms suffers from low recall, while an unconstrained flexible search for lemmas yields a loss in precision, we suggest a procedure aimed at maximizing precision in the identification of MWEs within a flexible search. Our method builds on the idea that internal variability can be modelled via the novel introduction of variation patterns, which work over POS patterns, and can be used as working tools for controlling precision. We also compare the performance of variation patterns to that of association measures, and explore the possibility of using variation patterns in MWE extraction in addition to identification. Finally, we suggest that corpus-derived, pattern-related information can be included in the original MWE lexicon by means of an enriched coding and the creation of an XML-based repository of patterns.", acknowledgement = ack-nhfb, articleno = "7", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Anonymous:2013:R, author = "Anonymous", title = "Reviewers", journal = j-TSLP, volume = "10", number = "2", pages = "8:1--8:??", month = jun, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2483691.2499382", ISSN = "1550-4875", bibdate = "Mon Jul 1 18:16:29 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, articleno = "8", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Constant:2013:CCR, author = "Matthieu Constant and Joseph {Le Roux} and Anthony Sigogne", title = "Combining compound recognition and {PCFG--LA} parsing with word lattices and conditional random fields", journal = j-TSLP, volume = "10", number = "3", pages = "8:1--8:??", month = jul, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2483969.2483970", ISSN = "1550-4875", bibdate = "Mon Jul 8 17:25:06 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "The integration of compounds in a parsing procedure has been shown to improve accuracy in an artificial context where such expressions have been perfectly preidentified. This article evaluates two empirical strategies to incorporate such multiword units in a real PCFG-LA parsing context: (1) the use of a grammar including compound recognition, thanks to specialized annotation schemes for compounds; (2) the use of a state-of-the-art discriminative compound prerecognizer integrating endogenous and exogenous features. We show how these two strategies can be combined with word lattices representing possible lexical analyses generated by the recognizer. The proposed systems display significant gains in terms of multiword recognition and often in terms of standard parsing accuracy. Moreover, we show through an Oracle analysis that this combined strategy opens promising new research directions.", acknowledgement = ack-nhfb, articleno = "8", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Kim:2013:WSS, author = "Su Nam Kim and Timothy Baldwin", title = "Word sense and semantic relations in noun compounds", journal = j-TSLP, volume = "10", number = "3", pages = "9:1--9:??", month = jul, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2483969.2483971", ISSN = "1550-4875", bibdate = "Mon Jul 8 17:25:06 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "In this article, we investigate word sense distributions in noun compounds (NCs). Our primary goal is to disambiguate the word sense of component words in NCs, based on investigation of ``semantic collocation'' between them. We use sense collocation and lexical substitution to build supervised and unsupervised word sense disambiguation (WSD) classifiers, and show our unsupervised learner to be superior to a benchmark WSD system. Further, we develop a word sense-based approach to interpreting the semantic relations in NCs.", acknowledgement = ack-nhfb, articleno = "9", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Lau:2013:CTM, author = "Jey Han Lau and Timothy Baldwin and David Newman", title = "On collocations and topic models", journal = j-TSLP, volume = "10", number = "3", pages = "10:1--10:??", month = jul, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2483969.2483972", ISSN = "1550-4875", bibdate = "Mon Jul 8 17:25:06 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We investigate the impact of preextracting and tokenizing bigram collocations on topic models. Using extensive experiments on four different corpora, we show that incorporating bigram collocations in the document representation creates more parsimonious models and improves topic coherence. We point out some problems in interpreting test likelihood and test perplexity to compare model fit, and suggest an alternate measure that penalizes model complexity. We show how the Akaike information criterion is a more appropriate measure, which suggests that using a modest number (up to 1000) of top-ranked bigrams is the optimal topic modelling configuration. Using these 1000 bigrams also results in improved topic quality over unigram tokenization. Further increases in topic quality can be achieved by using up to 10,000 bigrams, but this is at the cost of a more complex model. We also show that multiword (bigram and longer) named entities give consistent results, indicating that they should be represented as single tokens. This is the first work to explicitly study the effect of n -gram tokenization on LDA topic models, and the first work to make empirical recommendations to topic modelling practitioners, challenging the standard practice of unigram-based tokenization.", acknowledgement = ack-nhfb, articleno = "10", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Shutova:2013:CML, author = "Ekaterina Shutova and Jakub Kaplan and Simone Teufel and Anna Korhonen", title = "A computational model of logical metonymy", journal = j-TSLP, volume = "10", number = "3", pages = "11:1--11:??", month = jul, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2483969.2483973", ISSN = "1550-4875", bibdate = "Mon Jul 8 17:25:06 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "The use of figurative language is ubiquitous in natural language texts and it is a serious bottleneck in automatic text understanding. A system capable of interpreting figurative expressions would be an invaluable addition to the real-world natural language processing (NLP) applications that need to access semantics, such as machine translation, opinion mining, question answering and many others. In this article we focus on one type of figurative language, logical metonymy, and present a computational model of its interpretation bringing together statistical techniques and the insights from linguistic theory. Compared to previous approaches this model is both more informative and more accurate. The system produces sense-level interpretations of metonymic phrases and then automatically organizes them into conceptual classes, or roles, discussed in the majority of linguistic literature on the phenomenon.", acknowledgement = ack-nhfb, articleno = "11", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Klebanov:2013:SPM, author = "Beata Beigman Klebanov and Jill Burstein and Nitin Madnani", title = "Sentiment profiles of multiword expressions in test-taker essays: The case of noun--noun compounds", journal = j-TSLP, volume = "10", number = "3", pages = "12:1--12:??", month = jul, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2483969.2483974", ISSN = "1550-4875", bibdate = "Mon Jul 8 17:25:06 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "The property of idiomaticity vs. compositionality of a multiword expression traditionally pertains to the semantic interpretation of the expression. In this article, we consider this property as it applies to the expression's sentiment profile (relative degree of positivity, negativity, and neutrality). Thus, while heart attack is idiomatic in terms of semantic interpretation, the sentiment profile of the expression (strongly negative) can, in fact, be determined from the strongly negative profile of the head word. In this article, we (1) propose a way to measure compositionality of a multiword expression's sentiment profile, and perform the measurement on noun-noun compounds; (2) evaluate the utility of using sentiment profiles of noun-noun compounds in a sentence-level sentiment classification task. We find that the sentiment profiles of noun-noun compounds in test-taker essays tend to be highly compositional and that their incorporation improves the performance of a sentiment classification system.", acknowledgement = ack-nhfb, articleno = "12", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Nakov:2013:SIN, author = "Preslav I. Nakov and Marti A. Hearst", title = "Semantic interpretation of noun compounds using verbal and other paraphrases", journal = j-TSLP, volume = "10", number = "3", pages = "13:1--13:??", month = jul, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2483969.2483975", ISSN = "1550-4875", bibdate = "Mon Jul 8 17:25:06 MDT 2013", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "We study the problem of semantic interpretation of noun compounds such as bee honey, malaria mosquito, apple cake, and stem cell. In particular, we explore the potential of using predicates that make explicit the hidden relation that holds between the nouns that form the noun compound. For example, mosquito that carries malaria is a paraphrase of the compound malaria mosquito in which the verb explicitly states the semantic relation between the two nouns. We study the utility of using such paraphrasing verbs, with associated weights, to build a representation of the semantics of a noun compound, for example, malaria mosquito can be represented as follows: carry (23), spread (16), cause (12), transmit (9), and so on. We also explore the potential of using multiple paraphrasing verbs as features for predicting abstract semantic relations such as CAUSE, and we demonstrate that using explicit paraphrases can help improve statistical machine translation.", acknowledgement = ack-nhfb, articleno = "13", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Editors:2013:E, author = "{The Editors}", title = "Editorial", journal = j-TSLP, volume = "10", number = "4", pages = "14:1--14:??", month = dec, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2556529", ISSN = "1550-4875", bibdate = "Thu Jan 9 10:56:30 MST 2014", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", acknowledgement = ack-nhfb, articleno = "14", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Meguro:2013:LCL, author = "Toyomi Meguro and Yasuhiro Minami and Ryuichiro Higashinaka and Kohji Dohsaka", title = "Learning to control listening-oriented dialogue using partially observable {Markov} decision processes", journal = j-TSLP, volume = "10", number = "4", pages = "15:1--15:??", month = dec, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2513145", ISSN = "1550-4875", bibdate = "Thu Jan 9 10:56:30 MST 2014", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Our aim is to build listening agents that attentively listen to their users and satisfy their desire to speak and have themselves heard. This article investigates how to automatically create a dialogue control component of such a listening agent. We collected a large number of listening-oriented dialogues with their user satisfaction ratings and used them to create a dialogue control component that satisfies users by means of Partially Observable Markov Decision Processes (POMDPs). Using a hybrid dialog controller where high-level dialog acts are chosen with a statistical policy and low-level slot values are populated by a wizard, we evaluated our dialogue control method in a Wizard-of-Oz experiment. The experimental results show that our POMDP-based method achieves significantly higher user satisfaction than other stochastic models, confirming the validity of our approach. This article is the first to verify, by using human users, the usefulness of POMDP-based dialogue control for improving user satisfaction in nontask-oriented dialogue systems.", acknowledgement = ack-nhfb, articleno = "15", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Cai:2013:CCC, author = "Xiaoyan Cai and Wenjie Li and Renxian Zhang", title = "Combining co-clustering with noise detection for theme-based summarization", journal = j-TSLP, volume = "10", number = "4", pages = "16:1--16:??", month = dec, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2513563", ISSN = "1550-4875", bibdate = "Thu Jan 9 10:56:30 MST 2014", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "To overcome the fact that the length of sentences is short and their content is limited, we regard words as independent text objects rather than features of sentences in sentence clustering and develop two co-clustering frameworks, namely integrated clustering and interactive clustering, to cluster sentences and words simultaneously. Since real-world datasets always contain noise, we incorporate noise detection and removal to enhance clustering of sentences and words. Meanwhile, a semisupervised approach is explored to incorporate the query information (and the sentence information in early document sets) in theme-based summarization. Thorough experimental studies are conducted. When evaluated on the DUC2005-2007 datasets and TAC 2008-2009 datasets, the performance of the two noise-detecting co-clustering approaches is comparable with that of the top three systems. The results also demonstrate that the interactive with noise detection algorithm is more effective than the noise-detecting integrated algorithm.", acknowledgement = ack-nhfb, articleno = "16", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Blanco:2013:CSR, author = "Eduardo Blanco and Dan Moldovan", title = "Composition of semantic relations: Theoretical framework and case study", journal = j-TSLP, volume = "10", number = "4", pages = "17:1--17:??", month = dec, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2513146", ISSN = "1550-4875", bibdate = "Thu Jan 9 10:56:30 MST 2014", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Extracting semantic relations from text is a preliminary step towards understanding the meaning of text. The more semantic relations are extracted from a sentence, the better the representation of the knowledge encoded into that sentence. This article introduces a framework for the Composition of Semantic Relations (CSR). CSR aims to reveal more text semantics than existing semantic parsers by composing new relations out of previously extracted relations. Semantic relations are defined using vectors of semantic primitives, and an algebra is suggested to manipulate these vectors according to a CSR algorithm. Inference axioms that combine two relations and yield another relation are generated automatically. CSR is a language-agnostic, inventory-independent method to extract semantic relations. The formalism has been applied to a set of 26 well-known relations and results are reported.", acknowledgement = ack-nhfb, articleno = "17", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Sokolov:2013:LBO, author = "Artem Sokolov and Guillaume Wisniewski and Fran{\c{c}}ois Yvon", title = "Lattice {BLEU} oracles in machine translation", journal = j-TSLP, volume = "10", number = "4", pages = "18:1--18:??", month = dec, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2513147", ISSN = "1550-4875", bibdate = "Thu Jan 9 10:56:30 MST 2014", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "The search space of Phrase-Based Statistical Machine Translation (PBSMT) systems can be represented as a directed acyclic graph (lattice). By exploring this search space, it is possible to analyze and understand the failures of PBSMT systems. Indeed, useful diagnoses can be obtained by computing the so-called oracle hypotheses, which are hypotheses in the search space that have the highest quality score. For standard SMT metrics, this problem is, however, NP-hard and can only be solved approximately. In this work, we present two new methods for efficiently computing oracles on lattices: the first one is based on a linear approximation of the corpus bleu score and is solved using generic shortest distance algorithms; the second one relies on an Integer Linear Programming (ILP) formulation of the oracle decoding that incorporates count clipping constraints. It can either be solved directly using a standard ILP solver or using Lagrangian relaxation techniques. These new decoders are evaluated and compared with several alternatives from the literature for three language pairs, using lattices produced by two PBSMT systems.", acknowledgement = ack-nhfb, articleno = "18", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Oshea:2013:NBD, author = "James O'shea and Zuhair Bandar and Keeley Crockett", title = "A new benchmark dataset with production methodology for short text semantic similarity algorithms", journal = j-TSLP, volume = "10", number = "4", pages = "19:1--19:??", month = dec, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2537046", ISSN = "1550-4875", bibdate = "Thu Jan 9 10:56:30 MST 2014", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "This research presents a new benchmark dataset for evaluating Short Text Semantic Similarity (STSS) measurement algorithms and the methodology used for its creation. The power of the dataset is evaluated by using it to compare two established algorithms, STASIS and Latent Semantic Analysis. This dataset focuses on measures for use in Conversational Agents; other potential applications include email processing and data mining of social networks. Such applications involve integrating the STSS algorithm in a complex system, but STSS algorithms must be evaluated in their own right and compared with others for their effectiveness before systems integration. Semantic similarity is an artifact of human perception; therefore its evaluation is inherently empirical and requires benchmark datasets derived from human similarity ratings. The new dataset of 64 sentence pairs, STSS-131, has been designed to meet these requirements drawing on a range of resources from traditional grammar to cognitive neuroscience. The human ratings are obtained from a set of trials using new and improved experimental methods, with validated measures and statistics. The results illustrate the increased challenge and the potential longevity of the STSS-131 dataset as the Gold Standard for future STSS algorithm evaluation.", acknowledgement = ack-nhfb, articleno = "19", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", } @Article{Roy:2013:CCN, author = "Suman Deb Roy and Wenjun Zeng", title = "Cognitive canonicalization of natural language queries using semantic strata", journal = j-TSLP, volume = "10", number = "4", pages = "20:1--20:??", month = dec, year = "2013", CODEN = "????", DOI = "https://doi.org/10.1145/2539053", ISSN = "1550-4875", bibdate = "Thu Jan 9 10:56:30 MST 2014", bibsource = "http://portal.acm.org/; http://www.math.utah.edu/pub/tex/bib/tslp.bib", abstract = "Natural language search relies strongly on perceiving semantics in a query sentence. Semantics is captured by the relationship among the query words, represented as a network (graph). Such a network of words can be fed into larger ontologies, like DBpedia or Google Knowledge Graph, where they appear as subgraphs- fashioning the name subnetworks (subnets). Thus, subnet is a canonical form for interfacing a natural language query to a graph database and is an integral step for graph-based searching. In this article, we present a novel standalone NLP technique that leverages the cognitive psychology notion of semantic strata for semantic subnetwork extraction from natural language queries. The cognitive model describes some of the fundamental structures employed by the human cognition to construct semantic information in the brain, called semantic strata. We propose a computational model based on conditional random fields to capture the cognitive abstraction provided by semantic strata, facilitating cognitive canonicalization of the query. Our results, conducted on approximately 5000 queries, suggest that the cognitive canonicals based on semantic strata are capable of significantly improving parsing and role labeling performance beyond pure lexical approaches, such as parts-of-speech based techniques. We also find that cognitive canonicalized subnets are more semantically coherent compared to syntax trees when explored in graph ontologies like DBpedia and improve ranking of retrieved documents.", acknowledgement = ack-nhfb, articleno = "20", fjournal = "ACM Transactions on Speech and Language Processing (TSLP)", journal-URL = "https://dl.acm.org/loi/tslp", }