language modeling
Language Modeling with Shared Grammar
... The PTB dataset has parsing annotations, while OBWB dataset has no annotations. For the PTB dataset, we adopt the standard train / validation / test split. We build the vocabulary based on PTB, using one unknown token ...
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Feature Extraction for Native Language Identification Using Language Modeling
... Native Language Identification ...native language of authors of English texts written by non-native English speak- ...the language modeling approach and employs cross- entropy scores as ...
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Improvements in Stochastic Language Modeling
... IMPROVEMENTS IN STOCHASTIC LANGUAGE MODELING I M P R O V E M E N T S IN S T O C H A S T I C L A N G U A G E M O D E L I N G Ronald Rosenfeld and Xuedong Huang School of Computer Science Carnegie Mello[.] ...
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Learning to Create and Reuse Words in Open Vocabulary Neural Language Modeling
... that the preprocessed PTB is unrealistic for real lan- guage use in terms of word distribution. Since the vocabulary size is fixed to 10k, the word frequency does not exhibit a long tail. The wikiText-2 corpus is ...
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Script Induction as Language Modeling
... a language modeling task. By training a discriminative language model for this task, we attain improvements of up to 27 percent over prior methods on stan- dard narrative cloze ...
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Distributionally Robust Language Modeling
... for language modeling, train-test mismatches under subpopulation shifts are more broadly applicable to any task where there are trade-offs between potential test distri- butions, and potential test ...
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Parsing as Language Modeling
... The generative parsing model we presented in this paper is very powerful. In fact, we see that a gen- erative parsing model, LSTM-LM, is more effec- tive than discriminative parsing models (Dyer et al., 2016). We suspect ...
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On Using Written Language Training Data for Spoken Language Modeling
... On Using Written Language Training Data for Spoken Language Modeling On Using Written Language Training Data for Spoken Language Modeling R Schwartz, L Nguyen, F Kubala, G Chou, G Zavaliagkos t, J Mak[.] ...
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Book Reviews: The Oxford Handbook of Computational Linguistics edited by Ruslan Mitkov Reviewed by Peter Jackson; Readings in Machine Translation edited by Sergei Nirenburg, Harold Somers, and Yorick Wilks Reviewed by Elliott Macklovitch; Language Modeling for Information Retrieval edited by W Bruce Croft and John Lafferty Reviewed by Paul Thompson; Probabilistic Linguistics edited by Rens Bod, Jennifer Hay, and Stefanie Jannedy Reviewed by Patrick Juola
... on Language Modeling and Information Retrieval held May 31–June 1, 2001, at Carnegie Mellon University in Pittsburgh, ...the language-modeling ap- proach to information retrieval, which has ...
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Observations from Statistical Processing of BDNC01 Corpus
... Bangla language structures like English ...a language corpus are very important in language modeling and speech related research like speech ...
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HIVEC: A Hierarchical Approach for Vector Representation Learning of Graphs
... work of Mikolov et al. [1], traditionally used in language modeling, where representations of words is learnt using a deep learning method from the context where they occur in a sentence. The notion of ...
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Modeling non standard language
... to language modeling in general, and to modeling of non-standard language varieties in ...foreign language teaching, forensic linguistics, identi- fication of the author’s first ...
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Language and Dialect Discrimination Using Compression Inspired Language Models
... automated language and dialect ...man Language Technology Center of Excellence (JHU ...compression-inspired language modeling for language and dialect identifi- cation, using news, ...
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Author Index to the Proceedings of ANLP NAACL 2000 and the Student Research Workshop
... Techniques from language modeling may be of interest to anyone pursuing probabilistic modeling, including those interested in statistical parsing, information retrieval, machine translat[r] ...
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Noisy SMS Machine Translation in Low Density Languages
... 5-gram language model using the SRI language modeling toolkit (Stolcke, 2002) from the English monolingual News Commentary and News Crawl language modeling training data pro- vided for ...
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Geo Centric Language Models for Local Business Voice Search
... geo-centric language model generation that: adapts to the local business density; enables good local listing coverage; and requires only a limited number of language ...geo-centric language ...
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A Framework for Evaluating Model-driven Architecture
... domain-specific language to support the Context-Oriented Programming (COP) approach proposed by Hirschfeld et ...Java language proposed by Appeltauer et ...Unified Modeling Language (UML) ...
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Modeling Distributed Real-time Elevator System by Three Model Checkers
... NuSMV, which is more widely used, supports not only CTL and LTL but also PSL (Property Specification Language) [10]. In order to verify Petri nets, Szpyrka et al. who successfully employed two temporal logics ...
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Artificial Intelligence Markup Languange for Interactive Service HR Department
... The rapid development of information technology lately has entered almost all fields of life, this is marked by the number of computer users, both for the benefit of companies or businesses to things that are ...
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Agent Modeling Language (AML): A Comprehensive Approach to Modeling MAS
... expressive modeling lan- guage suitable for the development of commercial software solutions based on multi-agent ...a language that: (1) is built on proved technical foundations, (2) in- tegrates best ...
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