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word bigram language model

Detection of Intra-Sentential Code-Switching Points Using Word Bigram and Unigram Frequency Count

Detection of Intra-Sentential Code-Switching Points Using Word Bigram and Unigram Frequency Count

... two language models, one word bigram language model and one word unigram language ...The word bigram model was trained using 500,000 sentences from ...

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TINA: A Natural Language System for Spoken Language Applications

TINA: A Natural Language System for Spoken Language Applications

... 7 A bigram language model is commonly used in speech recognition systems, where bigram statistics frequency counts on adjacent word pairs are collected from words or word categories in s[r] ...

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Efficient Search for Inversion Transduction Grammar

Efficient Search for Inversion Transduction Grammar

... a language model as simple as bigram is generally ...guage model implies keeping at least n −1 bound- ary words in the dynamic programming table for a hypothetical translation of a source ...

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Word Association and MI Trigger based Language Modeling

Word Association and MI Trigger based Language Modeling

... It is found that proper MI-Trigger modeling is superior to word bigram model and the DD MI-Trigger models have better performance than the DI MI-Trigger models for the same window size..[r] ...

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A TAG based noisy channel model of speech repairs

A TAG based noisy channel model of speech repairs

... channel model described here in- volves two components. A language model de- fines a probability distribution P(X) over the source sentences X , which do not contain re- ...channel model ...

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Linguistic Theory in Statistical Language Learning

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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Using Word Support Model to Improve Chinese Input System

Using Word Support Model to Improve Chinese Input System

... i.e. bigram model (Lin and Tsai, 1987; Gu et ...statistical language model (SLM) used in the statistical approach requires less effort and has been widely adopted in com- mercial Chinese input ...

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A New Bigram-PLSA Language Model for Speech Recognition

A New Bigram-PLSA Language Model for Speech Recognition

... the bigram-PLSA model and other language ...of model parameters and the approximate time of each EM iteration are reported in this ...of model parameters for the bigram and ...

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A Polynomial Time Algorithm for Statistical Machine Translation

A Polynomial Time Algorithm for Statistical Machine Translation

... The approach employs the stochastic bracketing transduction grammar SBTG model we recently introduced to replace earlier word alignment channel models, while retaining a bigram language [r] ...

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Vocabulary Mismatch Avoidance Techniques

Vocabulary Mismatch Avoidance Techniques

... this model generates doc score considering three language models namely unigram , bigram and proximity of adjacent query term pair The proposed SSDM model is widens the scope of SDM ...

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Selecting Query Term Alternations for Web Search by Exploiting Query Contexts

Selecting Query Term Alternations for Web Search by Exploiting Query Contexts

... a word, then query expansion can produce the same effect as word ...possible word alterations, query expansion/reformulation will run the risk of adding many unrelated terms to the original query, ...

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A simple real-word error detection and correction using local word bigram and trigram

A simple real-word error detection and correction using local word bigram and trigram

... the word bigram or trigram ...considered word trigram ...for language modelling. If a word (W) in the sentence is unintended ( ...correct word is assumed to come from the members ...

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Learning Semantic Representations in a Bigram Language Model

Learning Semantic Representations in a Bigram Language Model

... these word to word dependencies do contain a semantic component, other factors, ...the bigram in terms of the similarity of the two words is explored. A model based on this assumption of ...

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From Paraphrase Database to Compositional Paraphrase Model and Back

From Paraphrase Database to Compositional Paraphrase Model and Back

... Extracting Training Data As before, training data was extracted from the XL section of PPDB. Similar to the procedure to create our Annotated- PPDB dataset, phrases were filtered such that only those with a word ...

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Improving Machine Translation Quality Estimation with Neural Network Features

Improving Machine Translation Quality Estimation with Neural Network Features

... We exploit SVR with different features to build the QE model. Experiments are performed on the development set of the WMT17 QE, task1. The experimental results of en-de and de-en are shown in Tables 3 and 4, ...

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Grounded Language Modeling for Automatic Speech Recognition of Sports Video

Grounded Language Modeling for Automatic Speech Recognition of Sports Video

... with word accuracy or error rate, such evaluations highlight a systems ability to recognize the more relevant con- tent words without being distracted by the more common stop ...

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Applying Collocation Segmentation to the ACL Anthology Reference Corpus

Applying Collocation Segmentation to the ACL Anthology Reference Corpus

... where T F (x) is the raw frequency of segment x in the corpus, N is the total number of documents in the corpus, and D(x) is the number of documents in which the segment x occurs. Table 4 presents the top 20 collocation ...

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Part of Speech Tagging in Manipuri: A Rule based Approach

Part of Speech Tagging in Manipuri: A Rule based Approach

... As per the literature, there is a few works related to POS tagging in Manipuri and other Tibeto-Burman languages in the Indian Sub-continent. In the year 2004, Sirajul Islam Choudhury, Leihaorambam Sarbajit Singh, Samir ...

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Learning Bilingual Word Representations by Marginalizing Alignments

Learning Bilingual Word Representations by Marginalizing Alignments

... learn word representations for both languages, a translation matrix relating these vec- tor spaces, as well as alignments at the same ...log-bilinear model are as follows. Where the original log-bilinear ...

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Automatic Recognition of Lyrics in Singing

Automatic Recognition of Lyrics in Singing

... and word-level n-gram language models. The phoneme language models are trained on the speech database ...large-vocabulary word-level language model is trained on a database of ...

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