statistical ngram language models
Tài liệu Báo cáo khoa học: "Reading Level Assessment Using Support Vector Machines and Statistical Language Models" pdf
... using statistical language models. In this paper, we also use support vectormachines to combine features from tradi-tional reading level measures, statistical language models, and other language ... relative toeach other.4.1 Statistical Language Models Statistical LMs predict the probability that a partic-ular word sequence will occur. The most commonlyused statistical language model is the ... of syntax. Our approach uses n-gram language models as a low-cost automatic ap-proximation of both syntactic and semantic analy-sis. Statistical language models (LMs) are used suc-cessfully...
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Tài liệu Báo cáo khoa học: "Generating statistical language models from interpretation grammars in dialogue systems" potx
... decades of statistical language modeling: Where do we go from here? In Proceed-ings of IEEE:88(8).Rosenfeld R. 2000. Incorporating Linguistic Structureinto Statistical Language Models. In ... comparison of in-grammar recognition performance.3 Language modellingTo generate the different trigram language models we used the SRI language modelling toolkit (Stol-cke, 2002) with Good-Turing ... movespecific statistical language models (DM-SLMs)by using GF to generate all utterances that arespecific to certain dialogue moves from our in-terpretation grammar. In this way we can pro-duce models...
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Báo cáo khoa học: "Enhancing Language Models in Statistical Machine Translation with Backward N-grams and Mutual Information Triggers" ppt
... of statistical machine translation: Parameter estimation. Computa-tional Linguistics, 19(2):263–311.Eugene Charniak, Kevin Knight, and Kenji Yamada.2003. Syntax-based language models for statistical machine ... as language models for statistical machine translation. In Proceed-ings of AMTA.Sylvain Raybaud, Caroline Lavecchia, David Langlois,and Kamel Sma¨ıli. 2009. New confidence measuresfor statistical ... Computational LinguisticsEnhancing Language Models in Statistical Machine Translationwith Backward N-grams and Mutual Information TriggersDeyi Xiong, Min Zhang, Haizhou LiHuman Language TechnologyInstitute...
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Tài liệu Báo cáo khoa học: "Incremental Syntactic Language Models for Phrase-based Translation" pptx
... research in statistical machine trans-lation has effectively used n-gram word sequence models as language models. Modern phrase-based translation using large scalen-gram language models generally ... to incorporate large-scale n-gram language models in conjunction withincremental syntactic language models. The added decoding time cost of our syntactic language model is very high. By increasing ... translation model. Instead, we incor-porate syntax into the language model.Traditional approaches to language models inspeech recognition and statistical machine transla-tion focus on the use of...
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Tài liệu Báo cáo khoa học: "The impact of language models and loss functions on repair disfluency detection" pptx
... language models trained from text or speech corpora of vari-ous genres and sizes. The largest available language models are based on written text: we investigate theeffect of written text language models ... dif-ferences among the different language models whenextended features are present are relatively small.We assume that much of the information expressedin the language models overlaps with the lexical ... information fromthe external language models by defining a rerankerfeature for each external language model. The valueof this feature is the log probability assigned by the language model to the candidate...
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Tài liệu Báo cáo khoa học: "An Empirical Investigation of Discounting in Cross-Domain Language Models" ppt
... 2006. MAP adaptation of stochasticgrammars. Computer Speech & Language, 20(1):41 –68.Jerome R. Bellegarda. 2004. Statistical language modeladaptation: review and perspectives. Speech Commu-nication, ... of EnglishBigrams. Computer Speech & Language, 5(1):19–54.Joshua Goodman. 2001. A Bit of Progress in Language Modeling. Computer Speech & Language, 15(4):403–434.Bo-June (Paul) Hsu ... N-gram Language Models Based onOrdinary Counts. In Proceedings of the ACL-IJCNLP2009 Conference Short Papers, pages 349–352.Ronald Rosenfeld. 1996. A Maximum Entropy Ap-proach to Adaptive Statistical...
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Tài liệu Báo cáo khoa học: "Improved Smoothing for N-gram Language Models Based on Ordinary Counts" doc
... Kneser-Ney andthose methods.1 Introduction Statistical language models are potentially usefulfor any language technology task that producesnatural -language text as a final (or intermediate)output. ... perplexity of any known methodfor estimating N-gram language models. Kneser-Ney smoothing, however, requiresnonstandard N-gram counts for the lower-order models used to smooth the highest-order model. ... best approach when language models based on ordinary counts are desired.ReferencesChen, Stanley F., and Joshua Goodman. 1998.An empirical study of smoothing techniques for language modeling....
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Tài liệu Báo cáo khoa học: "Statistical phrase-based models for interactive computer-assisted translation" pdf
... framework, real-time is re-quired.4 Phrase-based models The usual statistical translation models can beclassified as single-word based alignment models. Models of this kind assume that an input word ... framework (Och et al., 2003).Phrase-based models have proved to be very ad-equate statistical models for MT (Tom´as et al.,2005). In this work, the use of these models hasbeen extended to interactive ... Therefore, thesame techniques (translation models, decoder al-gorithm, etc.) which have been developed forSMT can be used in CAT.Note that the statistical models are defined atword level. However,...
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Tài liệu Báo cáo khoa học: "Guiding Statistical Word Alignment Models With Prior Knowledge" pdf
... max-imum entropy models for statistical machine translation. InProc. of ACL, pages 295–302.F. J. Och and H. Ney. 2003. A systematic comparison of vari-ous statistical alignment models. Computational ... Constrained Word Alignment Models The framework that we propose to incorporate sta-tistical constraints into word alignment models isgeneric. It can be applied to complicated models such IBM Model-4 ... translation performance.1 Introduction Statistical word alignment models learn word as-sociations between parallel sentences from statis-tics. Most models are trained from corpora in anunsupervised...
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Tài liệu Báo cáo khoa học: "Statistical Decision-Tree Models for Parsing*" ppt
... "Class-based n-gram models of natural language. " Computa- tional Linguistics, 18(4), pages 467-479. D. M. Magerman. 1994. Natural Language Pars- ing as Statistical Pattern Recognition. ... One of the important points of this work is that statistical models of natural language should not be restricted to simple, context-insensitive models. In a problem like parsing, where long-distance ... SPATTER's models SPATTER consists of three main decision-tree models: a part-of-speech tagging model, a node- extension model, and a node-labeling model. Each of these decision-tree models are...
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Tài liệu Báo cáo khoa học: "Web augmentation of language models for continuous speech recognition of SMS text messages" docx
... 2007. Large language models in machine translation. In Proceedingsof the 2007 Joint Conference on Empirical Meth-ods in Natural Language Processing and Com-putational Natural Language Learning ... Kneser-Ney smoothed n-gram models. IEEE Transac-tions on Audio, Speech and Language Processing,15(5):1617–1624.A. Stolcke. 1998. Entropy-based pruning of backoff language models. In Proc. DARPA ... wereselected for each language. The adaptation wasthought to take place off-line on a server.3.2.1 Data setsFor each language, the adaptation takes place ontwo baseline models, which are the...
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Báo cáo khoa học: "The use of formal language models in the typology of the morphology of Amerindian languages" potx
... grammars for modeling agglutinationin this language, but first we will present the for-mer class of languages and its acceptor automata.3.1 Linear context free languages andtwo-taped nondeterministic ... 2010.c2010 Association for Computational LinguisticsThe use of formal language models in the typology of the morphology ofAmerindian languagesAndr´es Osvaldo PortaUniversidad de Buenos Aireshugporta@yahoo.com.arAbstractThe ... natural representa-tion in terms of linear context-free languages.2 Quichua Santiague˜noThe quichua santiague˜no is a language of theQuechua language family. It is spoken in the San-tiago del...
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Báo cáo khoa học: "Faster and Smaller N -Gram Language Models" pptx
... novel language modelcaching technique that improves the queryspeed of our language models (and SRILM)by up to 300%.1 IntroductionFor modern statistical machine translation systems, language models ... with two different language models. Our first language model, WMT2010, was a 5-gram Kneser-Ney language model which storesprobability/back-off pairs as values. We trained this language model on ... and Smaller N -Gram Language Models Adam Pauls Dan KleinComputer Science DivisionUniversity of California, Berkeley{adpauls,klein}@cs.berkeley.eduAbstractN-gram language models are a major...
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Báo cáo khoa học: "Randomized Language Models via Perfect Hash Functions" pptx
... 2007.Compressing trigram language models with golombcoding. In Proceedings of EMNLP-CoNLL 2007,Prague, Czech Republic, June.P. Clarkson and R. Rosenfeld. 1997 . Statistical language modeling using ... 2007a. Randomised language modelling for statistical machine translation. In 45thAnnual Meeting of the ACL 2007, Prague.D. Talbot and M. Osborne. 2007b. Smoothed Bloomfilter language models: Tera-scale ... alignmenttemplate approach to statistical machine translation.Computational Linguistics, 30(4):417–449.Andreas Stolcke. 1998. Entropy-based pruning of back-off language models. In Proc. DARPA Broadcast...
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Báo cáo khoa học: "A Comparative Study of Parameter Estimation Methods for Statistical Natural Language Processing" potx
... linear models via a dynamic program. In the CMM, the local linear models are trained independently, while in the CRF model, the local models are trained jointly. We call these two linear models ... non-zero weight. 3.2 Language model adaptation Our experiments with LM adaptation are based on the work described in Gao et al. (2006). The va-riously trained language models were evaluated ... linear models local models because they dynamically combine the output of models that use only local features. While it is straightforward to apply the five es-timators to global models in the...
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- statistical natural language understanding
- web augmentation of language models
- generating statistical language models
- constructing statistical language models
- ngram language models based
- classbased ngram language models
- smoothing ngram language models
- syntax based language models for statistical machine translation
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