a pylonic decisiontree language model

... 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

... linguistically motivated grammar (a hand-crafted Head-driven Phrase Structure Grammar) and a statistical model estimating the probability of a parse tree. The language model is applied by means of an N-best ... create an artificial recognition task with manageable complexity. Our primary aim was to design a task which allows us to investigate the properties of our grammar-based approach and to compare ... prac- tice, but they have no theoretical justification. Our grammar-based language model is incorporated into the above expression as an additional probability P gr am (W ), weighted by a parameter...

Ngày tải lên: 17/03/2014, 02:20

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Ngày tải lên: 17/03/2014, 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

... 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 ... 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 ... 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....

Ngày tải lên: 20/02/2014, 07:20

... 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

... 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 ... by a chan- nel noise. The n-gram language model has achieved equal amounts of success in both tasks, e.g. n-character slice for text categorization by lan- guage (Cavnar and Trenkle, 1994) and...

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

... 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

... 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 ... June. Brian Roark, Murat Saraclar, and Michael Collins. 2007. Discriminative n-gram language modeling. computer speech and language. Computer Speech and Lan- guage, 21(2):373–392. Roni Rosenfeld, Stanley...

Ngày tải lên: 08/03/2014, 02:21

... 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

... 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...

Ngày tải lên: 08/03/2014, 21:20

... 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...

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