a discriminative language model

... Discriminative Language Model with Pseudo-Negative samples We propose a novel discriminative language model; a Discriminative Language Model with Pseudo- Negative samples (DLM-PN). In this model, pseudo-negative ... that they have the dis- advantage of being computationally expensive, and not all relevant features can be included. A discriminative language model (DLM) assigns a score to a sentence , measuring ... spe- cific applications and therefore were able to obtain real negative examples easily. For example, Roark (2007) proposed a discriminative language model, in which a model is trained so that a correct...

Ngày tải lên: 08/03/2014, 02:21

... NIST Language Recognition Evaluation database. 1 Introduction Spoken language and written language are similar in many ways. Therefore, much of the research in spoken language identification, ... Recognition Evaluation (LRE) data. The database was intended to establish a baseline of performance capability for language recognition of conversational tele- phone speech. The database contains recorded ... 2003. Acoustic, Pho- netic and Discriminative Approaches to Automatic language recognition, In Proc. of Eurospeech Masahide Sugiyama. 1991. Automatic language recog- nition using acoustic features ,...

Ngày tải lên: 20/02/2014, 15:20

... Proceedings of the Human Language Technology Workshop, 272-277. ARPA. Raymond Lau, Ronald Rosenfeld, and Salim Roukos. 1993. Trigger-based language models: a maximum entropy approach. In Proceedings ... University, Baltimore, MD. Frederick Jelinek, John Lafferty, David M. Mager- man, Robert Mercer, Adwait Ratnaparkhi, Salim Roukos. 1994. Decision Tree Parsing using a Hid- den Derivational Model. ... those assigned man- ually in the Penn Treebank (Marcus95) after under- going headword percolation and binarization. All four LMs predict a word wk and they were implemented using the Maximum...

Ngày tải lên: 22/02/2014, 03:20

... features, as described below: a statistical language model and a measure of tense difficulty. 4.1 The language model The lexical difficulty of a text is quite an elaborate phenomenon to parameterise. ... poems as outliers). 4 Selection of lexical and syntactic variables Any text classification tasks require an object (here a text) to be parameterised into variables, whether qualitative or quantitative. ... Belgium thomas.francois@uclouvain.be Abstract Reading is known to be an essential task in language learning, but finding the ap- propriate text for every learner is far from easy. In this context, automatic...

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Ngày tải lên: 31/03/2014, 04:20

... total path 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. ... replaced by characters, we can treat words as a means to enhance character recog- nition accuracy. Such arguments stand at least for Chinese ASR since they evaluate on character error rate and ... parts randomly: 5K as the adaptation corpus and 5K as the testing set. We show the ASR char- acter accuracy results after lexicon adaptation by the proposed approach in Table 3. LAICA-1 LAICA-2 A...

Ngày tải lên: 20/02/2014, 07:20

... signif- icantly. Bear in mind that Charniak et al. (2003) in- tegrated Charniak’s language model with the syntax- based translation model Yamada and Knight pro- posed (2001) to rescore a tree-to-string ... Stochastic analysis of lexical and semantic enhanced structural language model. The 8th International Colloquium on Grammatical Inference (ICGI), 97-111. K. Yamada and K. Knight. 2001. A syntax-based ... (EMNLP), 858-867. E. Charniak. 2001. Immediate-head parsing for language models. The 39th Annual Conference on Association of Computational Linguistics (ACL), 124-131. E. Charniak, K. Knight and K. Yamada. 2003....

Ngày tải lên: 20/02/2014, 04:20

... and Linda C. 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. ... n-grams: C(ab) − C(ab∗). A( ab) = max(1, K(C(ab) − C(ab∗))) A different K constant is chosen for each n-gram order. Using this formulation as an interpolated 5- gram language model gives a cross ... Speech and Language. R. Kneser and H. Ney. 1995. Improved backing-off for m-gram language modeling. In International Confer- ence on Acoustics, Speech, and Signal Processing. David J. C. Mackay and...

Ngày tải lên: 20/02/2014, 09:20

... com- pression tasks achieved a significant com- pression rate without any loss. 1 Introduction There has been an increase in available N -gram data and a large amount of web-scaled N-gram data has been ... the ACL-IJCNLP 2009 Conference Short Papers, pages 341–344, Suntec, Singapore, 4 August 2009. c 2009 ACL and AFNLP A Succinct N-gram Language Model Taro Watanabe Hajime Tsukada Hideki Isozaki NTT ... Communication Science Laboratories 2-4 Hikaridai Seika-cho Soraku-gun Kyoto 619-0237 Japan {taro,tsukada,isozaki}@cslab.kecl.ntt.co.jp Abstract Efficient processing of tera-scale text data is an important...

Ngày tải lên: 20/02/2014, 09:20

... translation, we develop a discriminative or- der model. An advantage of such a model is that we can easily combine different kinds of features (such as syntax-based and surface-based), and that ... Distortion models for statistical machine translation. In ACL. D. Chiang. 2005. A hierarchical phrase-based model for statis- tical machine translation. In ACL. M. Collins. 2000. Discriminative reranking ... inference and train- ing of context-rich syntactic translation models. In ACL. P. Koehn. 2004. Pharaoh: A beam search decoder for phrase- based statistical machine translation models. In AMTA. R....

Ngày tải lên: 20/02/2014, 12:20

... noisy channel paradigm, where the syntactic language model has the task of modeling a distribution over strings in the lan- guage, in a very similar way to traditional n-gram language models. ... Murat Saraclar, and Michael Collins. 2005. Dis- criminative n-gram language modeling. Computer Speech and Language. submitted. Brian Roark. 200 1a. Probabilistic top-down parsing and lan- guage modeling. ... HLT-NAACL 2004. Brian Roark, Murat Saraclar, and Michael Collins. 200 4a. Cor- rective language modeling for large vocabulary ASR with the perceptron algorithm. In Proc. ICASSP, pages 749–752. Brian...

Ngày tải lên: 20/02/2014, 15:20

... Universal Grammar and American Sign Language: Setting the Null Argument Parameters. Dordrecht: Kluwer Academic Publishers. MacWhinney, B., & Snow, C. (1985). The Child Language Data Exchange ... form a 'maximal' phrase or XP. Lexical items are inserted as soon as the appropriate X ° heads (or XPs, for pro-forms) become available. Each time a structural unit is built, and each ... while leaving the NPL and NPI parameters set at the default (negative) values. FELICITY can also be used to address theories pertaining to other aspects of language acquisition that appear slightly...

Ngày tải lên: 20/02/2014, 21:20

... Ducharme, P. Vincent, and C. Jauvin. 2003. A Neural Probabilistic Language Model. Journal of Machine Learning Research, 3:1137–1155. A. Berger, V. Della Pietra, and S. Della Pietra. 1996. A Maximum ... Discrimi- native n-gram Language Modeling. Computer, Speech and Language, 21:373–392. R. Rosenfeld. 1994. Adaptive Statistical Language Mod- elling: A Maximum Entropy Approach. Ph.D. thesis, Carnegie ... Rosenfeld. 1996. A Maximum Entropy Approach to Adaptive Statistical Language Modeling. Computer, Speech and Language, 10:187–228. A. Stolcke. 2002. SRILM – An Extensible Language Modeling Toolkit....

Ngày tải lên: 07/03/2014, 22:20

... Lee, L. S. et al. (1990). A Mandarin Dictation Machine Based Upon A Hierarchical Recognition Approach and Chinese Natural Language Analysis, IEEE Trans. on Pattern Analysis and Machine Intelligence, ... unification granunar and Markov language model are integrated in a word lattice parsing algorithm based on an augmented chart, and the island-driven parsing concept is combined with various ... correct rate of recognition can be as high as 98.3%. This indicates that the language processor based on the integration of the unification grammar and the Markov language model can in fact be...

Ngày tải lên: 08/03/2014, 07:20

... Information Retrieval and Filtering: An Empirical Basis for Grammatical Rules. Information Processing & Management, May. M. Magerman. 1996 Learning Grammatical Struc- ture Using Statistical ... Programs for Machine Learning. San Mateo, CA. Morgan Kaufmann. 3. Richards, D. Landgrebe and P. Swain. 1981 On the accuracy of pixel relaxation labelling. IEEE Transactions on System, Man and Cybernetics. ... All this makes that the performance cannot reach 100%, and that an accurate analysis of the noise in WS3 corpus should be performed to estimate the actual upper bound that a tagger can achieve...

Ngày tải lên: 08/03/2014, 21:20

... Ginsparg, J. M., A Robust Portable Natural Language Data Base Interface, Proc. Conf. Applied Natural Language Processing, 1983, pp.25-30. Grosz, B. J., TEAM: A Transportable Natural- Language ... A slot represents a relationship to another class using a $class facet and mapping information to the database schema using a Sstorage facet. The value of a Sstorage facet denotes the class ... have an attribute relationship. The phrase 'commodity A& apos; can modify the phrase 'to sell' both semantically and (Geneva) (commodity A) (to sell) (retailer) (name) S(Sales)...

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