discriminative syntactic language modeling

... Jelinek. 2000. Structured language modeling. Computer Speech and Language, 14(4):283–332. Ciprian Chelba. 2000. Exploiting Syntactic Structure for Nat- ural Language Modeling. Ph.D. thesis, The ... incorporates syntactic language models into a speech recognizer. These methods have almost ex- clusively worked within the noisy channel paradigm, where the syntactic language model has the task of modeling ... presented in this paper are a first step in examining the potential utility of syntactic features for discriminative language modeling for speech recognition. We tried two possible sets of features derived...

Ngày tải lên: 20/02/2014, 15:20

... smoothing techniques for language mod- eling. In Proceedings of the Association for Computa- tional Linguistics. Colin Cherry and Chris Quirk. 2008. Discriminative, syntactic language modeling through ... experiments on 1000- best lists from Moses using our syntactic language model as a feature. We did not find that the use of our syntactic language model made any statis- tically significant increases ... Word-lattice Parsing: Tech- niques for Integrated Syntactic Language Modeling. Ph.D. thesis, Brown University. Kenneth Heafield. 2011. Kenlm: Faster and smaller language model queries. In Proceedings of...

Ngày tải lên: 19/02/2014, 19:20

... Singapore, 2-7 August 2009. c 2009 ACL and AFNLP Discriminative Lexicon Adaptation for Improved Character Accuracy – A New Direction in Chinese Language Modeling Yi-cheng Pan Speech Processing Labratory National ... probability mass. This can be amended by involving the discriminative language model adaptation in the iteration, which results in a unified language model and lexicon adaptation framework. This ... Computer Processing of Oriental Languages, 12(1):99–121. Jianfeng Gao, Joshua Goodman, Mingjing Li, and Kai- Fu Lee. 2002. Toward a unified approach to statis- tical language modeling for Chinese. ACM...

Ngày tải lên: 20/02/2014, 07:20

... Saraclar. 2005. Discrimina- tive syntactic language modeling for speech recogni- tion. In ACL. Denis Filimonov and Mary Harper. 2009. A joint language model with fine-grain syntactic tags. In EMNLP. Yoav ... generative and discrimi- native language models. For generative LMs, the syntactic information must be part of the generative process. Structured language modeling incorporates syntactic parse trees to ... ICASSP. Brian Roark, Murat Saraclar, and Michael Collins. 2007. Discriminative n-gram language modeling. Computer Speech & Language, 21(2). K. Sagae and A. Lavie. 2006. A best-first probabilis- tic...

Ngày tải lên: 16/03/2014, 19:20

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Ngày tải lên: 23/03/2014, 20:20

... to incorporate large- scale n-gram language models in conjunction with incremental syntactic language models. The added decoding time cost of our syntactic language model is very high. By increasing ... parsing for language modeling, but do not use this language model in a translation system. Our work, in contrast to the above approaches, explores the use of incremental syntactic language models ... Jelinek. 2000. Structured language modeling. Computer Speech and Language, 14(4):283–332. Stanley F. Chen and Joshua Goodman. 1998. An empir- ical study of smoothing techniques for language mod- eling....

Ngày tải lên: 20/02/2014, 04:20

... before, the user can take a break and then the system continues with the next epoch. 3 Language Modeling Language modeling is important for many text pro- cessing applications, e.g., speech recognition ... and M. Fried-Oken. 2010. Scanning methods and language modeling for binary switch typing. In Proceedings of the NAACL HLT 2010 Workshop on Speech and Language Pro- cessing for Assistive Technologies, ... confusing. Finally, language model integration with RSVP is relatively straightforward, as we shall demonstrate. See Roark et al. (2010) for methods integrating language modeling into grid scanning. 2...

Ngày tải lên: 20/02/2014, 05:20

... the language model and the local tree order model outperformed either model by a large margin. This indicates that combin- ing syntactic (from the LTOM model) and surface- based (from the language ... WA kristout@microsoft.com Abstract We present a global discriminative statistical word order model for machine translation. Our model combines syntactic movement and surface movement information, and is discriminatively trained ... 9–16, Prague, Czech Republic, June 2007. c 2007 Association for Computational Linguistics A Discriminative Syntactic Word Order Model for Machine Translation Pi-Chuan Chang ∗ Computer Science Department Stanford...

Ngày tải lên: 20/02/2014, 12:20

... Language, 8:1–38. B. Roark, M. Saraclar, and M. Collins. 2007. Discrimi- native n-gram Language Modeling. Computer, Speech and Language, 21:373–392. R. Rosenfeld. 1994. Adaptive Statistical Language ... Entropy Approach to Adaptive Statistical Language Modeling. Computer, Speech and Language, 10:187–228. A. Stolcke. 2002. SRILM – An Extensible Language Modeling Toolkit. In Proceedings of the ... Hierarchical Distributed Language Model. In Advances in Neural Information Processing Systems 21. H. Ney, U. Essen, and R. Kneser. 1994. On Structur- ing Probabilistic Dependences in Stochastic Language Modeling. ...

Ngày tải lên: 07/03/2014, 22:20

... accurate word n-gram language model directly from characters of arbitrary language, without any “word” indications. 1 Introduction “Word” is no trivial concept in many languages. Asian languages such ... by the character HPYLM according to (4). This language model, which we call Nested Pitman-Yor Language Model (NPYLM) hereafter, is the hierarchical language model shown in Fig- ure 2, where the ... Kneser-Ney) language model, with an accurate character ∞-gram Pitman-Yor spelling model embedded in word models. Further- more, it can be viewed as a method for building a high-performance n-gram language...

Ngày tải lên: 17/03/2014, 01:20

... relationship, much like traditional language models, using con- ditional probability distributions. Unlike tradi- tional language models, however, our grounded language models condition the probability ... for improving speech recognition in video. The method uses grounded language modeling, an extension of tradition lan- guage modeling in which the probability of a word is conditioned not only ... work, we will examine the ability of grounded language models to improve perform- ance for other natural language tasks that exploit text based language models, such as Machine Translation....

Ngày tải lên: 17/03/2014, 02:20

... dependency and predictive clustering for language modeling. In EMNLP 2002. Gao. J., Yu, H., Yuan, W., and Xu, P. 2005. Minimum sample risk methods for language modeling. In HLT/EMNLP 2005. Osborne, ... perceptron algorithm. In HLT-NAACL 2004. 21-24. Collins, Michael and Terry Koo 2005. Discriminative reranking for natural language parsing. Computational Linguistics 31(1): 25-69. Duda, Richard O, ... Statistics, 9(2): 319-337. Roark, Brian, Murat Saraclar and Michael Collins. 2004. Corrective language modeling for large vo- cabulary ASR with the perceptron algorithm. In ICASSP 2004. Schapire,...

Ngày tải lên: 17/03/2014, 04:20

... not based on any syntactic annotation: the dependency struc- ture used in language modeling was learned directly from data in an unsupervised manner, subject to two weak syntactic constraints ... this method, no manual syntactic annotation is required, thereby opening up the possibility for building a language model that performs well on a wide variety of data and languages. The proposed ... structure acquisition. One basic approach to using linguistic structure for language modeling is to extend the conventional language model P(W) to P(W, T), where T is a parse tree of W. The extended...

Ngày tải lên: 17/03/2014, 06:20

... size is approximately 120k words. 3 Optimizing Document Clustering for Language Modeling For the purpose of language modeling, the topic la- bels assigned to a document or segment of a doc- ... contribution 172 Dynamic Nonlocal Language Modeling via Hierarchical Topic-Based Adaptation Radu Florian and David Yarowsky Computer Science Department and Center for Language and Speech Processing, ... smooth language models are computed for each node n different than the root by three-way interpolating between the m-gram language model in the parent parent(n), the (m - 1)-gram smooth language...

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