[PDF] Top 20 Statistical Input Method based on a Phrase Class n gram Model
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Statistical Input Method based on a Phrase Class n gram Model
... A phrase model has less cross-entropy than a word model (Mori et ...1997). Phrase modeling makes a more accurate language ...of phrase models is larger than that of word models, because ... See full document
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A Hybrid Word Alignment Model for Phrase Based Statistical Machine Translation
... The proposed Rule based aligner aligns Named Entities (NEs) and chunks. For NE alignment, we first identify NEs from the source side (i.e. English) using Stanford NER. The NEs on the target side (i.e. Bengali) are ... See full document
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Multi Class Composite N gram Language Model for Spoken Language Processing Using Multiple Word Clusters
... in class N-grams, POS in- formation is sometimes ...considered based on word connectivity by the reflection neighboring charac- teristics in the ...this method, the same vector is assigned to ... See full document
8
Statistical Phrase Based Translation
... a phrase-based system, tools and resources are freely available for re- searchers in the ...the phrase translation table. We found ex- traction heuristics based on word alignments to be better ... See full document
7
A Phrase Based Statistical Model for SMS Text Normalization
... a phrase-based statis- tical model for SMS text ...similar phrase-based statistical MT method (Koehn et ...using n-gram statistics, which is widely-used in ... See full document
8
A Hierarchical Phrase Based Model for Statistical Machine Translation
... state-of-the-art phrase-based system Pharaoh (Koehn et ...tion model on the FBIS corpus (7.2M+9.2M words); for the language model, we used the SRI Language Modeling Toolkit to train a trigram ... See full document
8
Efficient Solutions for Word Reordering in German English Phrase Based Statistical Machine Translation
... reordering model that predicts what in- put word should be translated at a given decod- ing state (Bisazza, 2013; Bisazza and Federico, ...The model is similar to the one proposed by Visweswariah et ...the ... See full document
12
N gram based Tense Models for Statistical Machine Translation
... effective method to model above ...tense n-gram model is constructed. Such model can be used to estimate the rationality of tense combina- tion in a sentence and thus supervise ... See full document
10
Effective Utterance Classification with Unsupervised Phonotactic Models
... Different possible classification algorithms can be used in our utterance classification method. For the experiments reported here we use the BoosTexter classifier (Schapire and Singer, 2000). Among the ... See full document
7
Neural Machine Translation Leveraging Phrase based Models in a Hybrid Search
... with phrase-based ...translations based on the current and accumulated attention weights of the NMT decoder ...NMT model score was used in a log-linear model with standard ... See full document
10
Syntax Based Word Ordering Incorporating a Large Scale Language Model
... for statistical machine ...of input words (Wan et ...an N-gram language model, which has been used by text generation systems to improve ...an N-gram model by ... See full document
11
Maximum Entropy Based Phrase Reordering Model for Statistical Machine Translation
... of phrase-based SMT is that phrase cohere across two languages (Fox, 2002), which means phrases in one language tend to be moved together during ...the class. For feature f and class c, ... See full document
8
A Tree to String Phrase based Model for Statistical Machine Translation
... Though phrase-based SMT has achieved high translation quality, it still lacks of generaliza- tion ability to capture word order differences between ...general method for tree-to-string phrase- ... See full document
8
A Phrase Based,Joint Probability Model for Statistical Machine Translation
... in statistical machine translation (MT) (Brown et ...generative model explains how source words are mapped into target words and how target words are re-ordered to yield well-formed target ...template- ... See full document
7
Letter N Gram based Input Encoding for Continuous Space Language Models
... standard n-gram language models (Bengio et ...rescore n-best lists of a ma- chine translation system during tuning and testing ...smaller n- gram model (Le et ...language ... See full document
10
Data Driven Response Generation in Social Media
... the input status- post s using a log-linear combination of feature ...conditional phrase-translation probabilities in both directions, P(s | r) and P (r | s), which ensure r is an appropriate response to s ... See full document
11
Neural Network Based Bilingual Language Model Growing for Statistical Machine Translation
... a phrase-based SMT system is concatenation of phrases from the phrase table, whose probabilities can be calculated by ...CSLM. Based on this obser- vation, a novel neural network based ... See full document
7
The Operation Sequence Model—Combining N Gram Based and Phrase Based Statistical Machine Translation
... our model combines the benefits of both of the frameworks and removes their ...state-of-the-art phrase-based (Moses and Phrasal) and N-gram-based (Ncode) systems on three ... See full document
30
The RWTH Aachen University English Romanian Machine Translation System for WMT 2016
... models: Phrase translation probabilities and lexical smoothing in both directions, word and phrase penalty, distance- based reordering model, n -gram target language models and ... See full document
6
Grammatical Machine Translation
... from n-gram based automatic evaluation scores for a moment, and investigate the possible contributions of incorporating a grammar-based generator into a dependency-based SMT ...SMT ... See full document
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