statistical language
Statistical Language Processing Using Hidden Understanding Models
... STATISTICAL LANGUAGE PROCESSING USING HIDDEN UNDERSTANDING MODELS S T A T I S T I C A L L A N G U A G E P R O C E S S I N G U S I N G H I D D E N U N D E R S T A N D I N G M O D E L S Scott Miller C o[.] ...
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Exploring the Process of Statistical Language Learning
... auditory language sequence and the n-back task ...of statistical language learning, and statistical learning more ...that statistical learning involves memory-related processes ...
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Japanese OCR Error Correction using Character Shape Similarity and Statistical Language Model
... Japanese OCR Error Correction using Character Shape Similarity and Statistical Language Model Japanese O C R Error Correction using Character Shape Similarity and Statistical Language Model M a s a a[.] ...
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Unsupervised morph segmentation and statistical language models for vocabulary expansion
... 2.2 Statistical language models over morphs As statistical language models, two state-of-the- art models were ...These language models were trained on a corpus, where one segmented word ...
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A Hybrid Approach to Adaptive Statistical Language Modeling
... A HYBRID APPROACH TO ADAPTIVE STATISTICAL LANGUAGE MODELING A HYBRID APPROACH TO ADAPTIVE STATISTICAL LANGUAGE MODELING Ronald Rosenfeld School of Computer Science C a r n e g i e M e l l o n U n i v[.] ...
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Japanese OCR Error Correction using Character Shape Similarity and Statistical Language Model
... It consists of a statistical OCR model, an approximate word matching method using character shape similarity, and a word segmentation algorithm using a statistical language model.. By us[r] ...
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A Random Text Model for the Generation of Statistical Language Invariants
... natural language data, also slightly differ- ing exponents in the range of about ...in language data, noticing that Zipf’s law holds only for the medium range of ranks, whereas the curve is flatter for very ...
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Generalized Algorithms for Constructing Statistical Language Models
... A word lattice is a weighted finite automaton (WFA) output by the recognizer for a particular utterance. It contains typically a very large set of alternative transcrip- tion sentences for that utterance with the ...
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Exploring Asymmetric Clustering for Statistical Language Modeling
... The discussion of the ACM in this paper is an extension of several studies below. The first similar cluster model was presented by Goodman and Gao [2000] in which the clustering techniques were combined with Stolcke’s ...
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Annealing Techniques For Unsupervised Statistical Language Learning
... of language structure that use dynamic programming to compute posteriors over hidden structure, such as hidden Markov models (HMMs) and stochastic context-free grammars ...
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Using Related Languages to Enhance Statistical Language Models
... lated language models are achieved when combin- ing the 30K-sentence Spanish model with the ...best-performing language model mix that used all three languages, Portuguese was weighted with a lambda of ...
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An Analysis of the Ability of Statistical Language Models to Capture the Structural Properties of Language
... to language model analysis that is more in- dependent from specific applications than previous reviews of language model ...of language that are mea- surable and ideally equally valid on real and ...
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Cross Lingual Lexical Triggers in Statistical Language Modeling
... In spite of their considerable success, some short- comings remain in the method used by Khudanpur and Kim (2002). Specifically, stochastic translation lexicons estimated using the IBM method (Brown et al., 1993) from a ...
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Statistical language learning
... " or "can participants learn this structure?" progressively loose interest in favour of questions such as "given several potential cues and interpretations available, under what specific[r] ...
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Linguistic Theory in Statistical Language Learning
... So t h e simple word bigram model not only em- ploys highly useful notions from linguistic theory, it implicitly employs the machinery of rewrite rules and derivations from formal langua[r] ...
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Book Reviews: Statistical Language Learning
... "Towards history-based grammars: Using richer models for probabilistic parsing." In Speech and Natural Language: Proceedings of a Workshop Held at Harriman, New York.. San Francisco, Cal[r] ...
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Stemming Algorithms: A Comparative Study and their Analysis
... languages, statistical language processing methods have been successfully used to improve the performance of IR ...based language independent stemmer ...
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Head Driven Statistical Models for Natural Language Parsing
... Earlier work that is of particular relevance considered the importance of relations between lexical heads for disambiguation in parsing. See Hindle and Rooth (1991) for one of the earliest pieces of research on this ...
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First Language Proficiency as a Facilitator in Foreign/ Second Language Acquisition: A Case Study in the Kingdom of Saudi Arabia
... new language may be ...using language that requires them to analyze, synthesize, and summarize, they can easily transfer these skills to a second ...first language (Burt, Peyton, & Adams, ...
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Observations from Statistical Processing of BDNC01 Corpus
... Bangla language structures like English yet. The statistical properties of a language corpus are very important in language modeling and speech related research like speech ...
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