incremental syntactic language models

... 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 ... (2007) use supertag n-gram LMs. Syntactic language models have also been explored with tree-based translation models. Charniak et al. (2003) use syntactic lan- guage models to rescore the output ... 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...

Ngày tải lên: 20/02/2014, 04:20

Ngày tải lên: 17/03/2014, 22:20

... 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 ... propose a simple generative, syntactic language model that conditions on overlap- ping windows of tree context (or treelets) in the same way that n-gram language models condition on overlapping ... 2005). At the same time, because n-gram language models only condition on a local window of linear word-level context, they are poor models of long-range syntactic dependencies. Although sev- eral...

Ngày tải lên: 19/02/2014, 19:20

... 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 the effect of written text language models ... dif- ferences among the different language models when extended features are present are relatively small. We assume that much of the information expressed in the language models overlaps with the lexical ... information from the external language models by defining a reranker feature for each external language model. The value of this feature is the log probability assigned by the language model to the candidate...

Ngày tải lên: 20/02/2014, 04:20

... of English Bigrams. 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 ... Association for Computational Linguistics An Empirical Investigation of Discounting in Cross-Domain Language Models Greg Durrett and Dan Klein Computer Science Division University of California, Berkeley {gdurrett,klein}@cs.berkeley.edu Abstract We ... 2006. MAP adaptation of stochastic grammars. Computer Speech & Language, 20(1):41 – 68. Jerome R. Bellegarda. 2004. Statistical language model adaptation: review and perspectives. Speech Commu- nication,...

Ngày tải lên: 20/02/2014, 04:20

... Kneser-Ney and those methods. 1 Introduction Statistical language models are potentially useful for any language technology task that produces natural -language text as a final (or intermediate) output. ... perplexity of any known method for estimating N-gram language models. Kneser-Ney smoothing, however, requires nonstandard 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. References Chen, Stanley F., and Joshua Goodman. 1998. An empirical study of smoothing techniques for language modeling....

Ngày tải lên: 20/02/2014, 09:20

... work that 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 ... traditional n-gram language models. The Structured Language Model (Chelba and Jelinek, 1998; Chelba and Jelinek, 2000; Chelba, 2000; Xu et al., 2002; Xu et al., 2003) makes use of an incremental shift-reduce ... words. Incremental top- down and left-corner parsing (Roark, 2001a; Roark, 2001b) and head-driven parsing (Charniak, 2001) approaches have directly used generative PCFG models as language models. ...

Ngày tải lên: 20/02/2014, 15:20

... 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 ... statistical language models. In this paper, we also use support vector machines to combine features from tradi- tional reading level measures, statistical language models, and other language pro- cessing ... it does not capture syntactic information. We believe that higher order n-gram models or class n-gram models can achieve better performance by captur- ing both semantic and syntactic information....

Ngày tải lên: 20/02/2014, 15:20

... comparison of in- grammar recognition performance. 3 Language modelling To generate the different trigram language models we used the SRI language modelling toolkit (Stol- cke, 2002) with Good-Turing ... decades of statistical language modeling: Where do we go from here? In Proceed- ings of IEEE:88(8). Rosenfeld R. 2000. Incorporating Linguistic Structure into Statistical Language Models. In Philosophical Transactions ... statistical language models (DM-SLMs) by using GF to generate all utterances that are specific to certain dialogue moves from our in- terpretation grammar. In this way we can pro- duce models that...

Ngày tải lên: 22/02/2014, 02:20

... 2007. Large language models in machine translation. In Proceedings of 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 ... 8 billion. 3 Speech Recognition Experiments We have trained language models on the in- domain data together with web data, and these models have been used in speech recognition ex- periments....

Ngày tải lên: 22/02/2014, 02:20

... grammars for modeling agglutination in this language, but first we will present the for- mer class of languages and its acceptor automata. 3.1 Linear context free languages and two-taped nondeterministic ... 2010. c 2010 Association for Computational Linguistics The use of formal language models in the typology of the morphology of Amerindian languages Andr ´ es Osvaldo Porta Universidad de Buenos Aires hugporta@yahoo.com.ar Abstract The ... natural representa- tion in terms of linear context-free languages. 2 Quichua Santiague ˜ no The quichua santiague˜no is a language of the Quechua language family. It is spoken in the San- tiago del...

Ngày tải lên: 07/03/2014, 22:20

... novel language model caching technique that improves the query speed of our language models (and SRILM) by up to 300%. 1 Introduction For 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 stores probability/back-off pairs as values. We trained this language model on ... Queries Decoders with integrated language models (Och and Ney, 2004; Chiang, 2005) score partial translation hypotheses in an incremental way. Each partial hy- pothesis maintains a language model context...

Ngày tải lên: 07/03/2014, 22:20

... explore a dependency language model to improve translation quality. To some ex- tent, these syntactically-informed language models are consistent with syntax-based translation models in capturing ... build linguistically-informed language models. For example, Charniak et al. (2003) present a syntax-based language model for machine transla- tion which is trained on syntactic parse trees. Again, Shen ... or even trillions of English words, huge language models are built in a distributed man- ner (Zhang et al., 2006; Brants et al., 2007). Such language models yield better translation results but at...

Ngày tải lên: 07/03/2014, 22:20

... (lossless) lan- guages models and our randomized language model. Note that the standard practice of measuring per- plexity is not meaningful here since (1) for efficient computation, the language model ... 2007. Compressing trigram language models with golomb coding. In Proceedings of EMNLP-CoNLL 2007, Prague, Czech Republic, June. P. Clarkson and R. Rosenfeld. 1997 . Statistical language modeling using ... pruning of back- off language models. In Proc. DARPA Broadcast News Transcription and Understanding Workshop, pages 270–274. D. Talbot and M. Osborne. 2007a. Randomised language modelling for...

Ngày tải lên: 08/03/2014, 01:20

... . Class-based models. In many applications, it is nat- ural and convenient to construct class-based language models, that is models based on classes of words (Brown et al., 1992). Such models are ... experi- mental results demonstrating its efficiency. Representation of language models by WFAs. Clas- sical -gram language models admit a natural representa- tion by WFAs in which each state encodes ... re- lated to the construction of language models. We present new and efficient algorithms to address these more gen- eral problems. Counting. Classical language models are constructed by deriving...

Ngày tải lên: 08/03/2014, 04:22

... LMs are devised to capture typical lexical and syntactic constructions that characterize the style of speech transcripts. Compared to standard language models, hy- brid LMs generalize better to the ... Hoang. 2007. Factored translation models. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), ... Monz. 2011. Statistical Machine Translation with Local Language Models. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pages 869–879, Edinburgh, Scotland,...

Ngày tải lên: 08/03/2014, 21:20

Ngày tải lên: 16/03/2014, 19:20

Ngày tải lên: 17/03/2014, 00:20

Ngày tải lên: 17/03/2014, 04:20

Ngày tải lên: 17/03/2014, 04:20