unsupervised language model adaptation incorporating named entity information

Ngày tải lên: 21/06/2014, 20:20

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Ngày tải lên: 22/06/2014, 00:20

... transferred across languages, to cross- lingual language modeling and translation lexicon adaptation. Recently, Gong and Zhou (2010) also applied topic modeling into domain adaptation in SMT. ... weblog. According to adaptation emphases, domain adap- tation in SMT can be classified into translation mod- el adaptation and language model adaptation. Here we focus on how to adapt a translation model, which is ... Vogel. 2006. Distributed Language Modeling for N-best List Re-ranking. In Proc. of EMNLP 2006, pages 216-223. Bing Zhao, Matthias Eck and Stephan Vogel. 2004. Language Model Adaptation for Statistical...

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Ngày tải lên: 31/03/2014, 21:20

... 2003). Topic modeling has received some use in SMT, for in- stance Bilingual LSA adaptation (Tam et al., 2007), and the BiTAM model (Zhao and Xing, 2006), which uses a bilingual topic model for ... Korea, 8-14 July 2012. c 2012 Association for Computational Linguistics Topic Models for Dynamic Translation Model Adaptation Vladimir Eidelman Computer Science and UMIACS University of Maryland College ... topic-specific contexts, where topics are induced in an unsupervised way using topic models; this can be thought of as inducing subcorpora for adaptation with- out any human annotation. We use these...

Ngày tải lên: 19/02/2014, 19:20

... 5-gram/2-SLM+2-gram/4-SLM+5- gram/PLSA language model improves both signif- icantly. Bear in mind that Charniak et al. (2003) in- tegrated Charniak’s language model with the syntax- based translation model Yamada and ... Large language models in ma- chine translation. The 2007 Conference on Empirical Methods in Natural Language Processing (EMNLP), 858-867. E. Charniak. 2001. Immediate-head parsing for language models. ... Dis- tributed language modeling for N-best list re-ranking. The 2006 Conference on Empirical Methods in Natu- ral Language Processing (EMNLP), 216-223. Y. Zhang, 2008. Structured language models for...

Ngày tải lên: 20/02/2014, 04:20

... to determine the named entity type of a proposed entity. We further describe the methods by which English language data can be used to bootstrap the NER process in other languages. We demonstrate ... 1 Introduction Named Entity Recognition (NER) has long been a major task of natural language processing. Most of the research in the field has been restricted to a few languages and almost ... that the derived models are continually improved and that increasingly many languages can be usefully modeled by this method. In order to make sure that the process is as language- independent...

Ngày tải lên: 20/02/2014, 09:20

... 2006. Unsupervised named- entity recognition: Generating gazetteers and resolving ambiguity. In 19th Canadian Conference on Artificial Intelligence. K. Nakano and Y. Hirai. 2004. Japanese named entity extraction ... external knowledge for named entity recognition. In EMNLP-CoNLL 2007. J. Kazama, Y. Miyao, and J. Tsujii. 2001. A maxi- mum entropy tagger with unsupervised hidden Markov models. In NLPRS 2001. T. ... Cafarella, D. Downey, A. M. Popescu, T. Shaked, S. Soderland, D. S. Weld, and A. Yates. 2005. Unsupervised named- entity extraction from the Web – an experimental study. Artificial Intelligence Journal. M....

Ngày tải lên: 20/02/2014, 09:20

... Linguistics Robust Extraction of Named Entity Including Unfamiliar Word Masatoshi Tsuchiya † Shinya Hida ‡ Seiichi Nakagawa ‡ † Information and Media Center / ‡ Department of Information and Computer ... of extracting Japanese named entities from IREX corpus and NHK corpus show the effective- ness of the proposed method. 1 Introduction It is widely agreed that extraction of named entity (henceforth, ... corpus and NHK corpus show the effectiveness of the proposed method. 2 Extraction of Japanese Named Entity 2.1 Task of the IREX Workshop The task of NE extraction of the IREX workshop (Sekine and...

Ngày tải lên: 20/02/2014, 09:20

... Goodman. 2001. A bit of progress in language modeling. Computer Speech and Language. R. Kneser and H. Ney. 1995. Improved backing-off for m-gram language modeling. In International Confer- ence ... Bauman Peto. 1995. A hierarchical Dirichlet language model. Natural Lan- guage Engineering, 1(3):1–19. Y.W. Teh. 2006. A hierarchical Bayesian language model based on Pitman-Yor processes. In Proceed- ings ... sure the probabilities are normalized. The interpolated models always incorporate the lower or- der distribution Pr(c|b) whereas the back-off models consider it only when the n-gram abc has not been observed...

Ngày tải lên: 20/02/2014, 09:20

... -gram language models are com- pressed into 10 GB, which is comparable to a lossy representation (Talbot and Brants, 2008). 2 N -gram Language Model We assume a back-off N-gram language model ... language model structure and word iden- tifiers. In Proc. of ICASSP 2003, volume 1. A. Stolcke. 1998. Entropy-based pruning of backoff language models. In Proc. of the ARPA Workshop on Human Language ... representation with block compression. N-gram language models of 42.65GB were compressed to 18.37GB. Finally, the 8-bit quantized N -gram language models are represented by 9.83GB of space. Table...

Ngày tải lên: 20/02/2014, 09:20

... necessar- ily provide useful information because, in many cases, the previous label of a named entity is “O”, which indicates a non -named entity. For 98.0% of the named entities in the training ... and prev -entity label are packed. model, which was originally proposed for disam- biguation models for parsing (Miyao and Tsujii, 2002). A feature forest model is a maximum en- tropy model defined ... use partial information on the preceding states. Consider the task of tag- ging entity and O -entity, where the latter tag is ac- tually O tags that distinguish the preceding named entity tags....

Ngày tải lên: 20/02/2014, 12:20

... However, many languages lack such resources. This paper presents an (almost) unsupervised learning algorithm for automatic discov- ery of Named Entities (NEs) in a resource free language, given ... similarity with a linear transliteration model. We first train a transliteration model on single- word NEs. During training, for a given NE in one language, the current model chooses a list of top ranked ... language. Identification of the entity s equivalence class of transliterations is important for obtaining its accurate time sequence. In order to keep to our objective of requiring as little language...

Ngày tải lên: 20/02/2014, 12:20

... statistical language modeling, and language identification. A typical LID system is illustrated in Figure 1 (Zissman, 1996), where language dependent voice tokenizers (VT) and lan- guage models ... called tokens; 2) A statistical language model which captures language dependent phonetic and phonotactic information from the sequences of tokens; 3) A language classifier which identifies ... semantic information in statistical language modeling , In Proc. of the IEEE, 88(8):1279-1296. M. W. Berry, S.T. Dumais and G.W. O’Brien. 1995. Using Linear Algebra for intelligent information...

Ngày tải lên: 20/02/2014, 15:20