[PDF] Top 20 Language Model Weight Adaptation Based on Cross-entropy for Statistical Machine Translation
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Language Model Weight Adaptation Based on Cross-entropy for Statistical Machine Translation
... feature’s weight represents its importance in the decoding procedure, such type of importance might vary for different datasets under a specific language ...of language model weight, ... See full document
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Adaptation of Statistical Machine Translation Model for Cross Lingual Information Retrieval in a Service Context
... is based on the rule-based XIP parser, where some heuristics specific to query processing have been integrated into English and French (but not Ger- man) grammars (Brun et ... See full document
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Perplexity Minimization for Translation Model Domain Adaptation in Statistical Machine Translation
... all translation model features, and a modified one that normalizes λ for each phrase pair (s, t) for p(t|s) and recomputes the lexical weights based on interpolated word translation ...on ... See full document
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Translation Model Adaptation for Statistical Machine Translation with Monolingual Topic Information
... with translation model adap- tation by making use of the topical context, so let us take a look at the recent research developmen- t on the application of topic models in ...bilingual translation ... See full document
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Connecting Phrase based Statistical Machine Translation Adaptation
... SMT adaptation means selecting useful part from mix-domain (mixture of in-domain and out-of- domain) data, for SMT performance ...in adaptation is about how to select the useful ...level adaptation: ... See full document
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Vector Space Model for Adaptation in Statistical Machine Translation
... The translation model (TM) was smoothed in both directions with KN smoothing (Chen et ...ing model (RM) (Galley and Manning, 2008), with a distortion limit of ... See full document
9
Using a Cross Language Information Retrieval System based on OHSUMED to Evaluate the Moses and KantanMT Statistical Machine Translation Systems
... two statistical machine translation (SMT) systems within a cross-language information retrieval (CLIR) architecture and examine if there is a correlation between translation ... See full document
5
Phrase Training Based Adaptation for Statistical Machine Translation
... on translation model (TM) ...who weight each sentence in the bitexts using features of meta-information and opti- mize a mapping from the feature vectors to weights using a translation quality ... See full document
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Incorporating Word and Subword Units in Unsupervised Machine Translation Using Language Model Rescoring
... German-Czech language pair are built based on the previously proposed unsupervised MT sys- tems, with some adaptations made to accom- modate the morphologically rich characteristics of German and Czech ... See full document
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Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing
... Maximum Entropy based Rule Selection Model for Syntax-based Statistical Machine Translation Qun Liu, Zhongjun He, Yang Liu and Shouxun Lin.. Indirect-HMM-based Hypothesis Alignment for C[r] ... See full document
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On line Language Model Biasing for Statistical Machine Translation
... LM adaptation for SMT. Snover et al. (2008) used a cross-lingual infor- mation retrieval (CLIR) system to select a subset of target documents “comparable” to the source docu- ment; bias LMs estimated from ... See full document
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A Topic Triggered Language Model for Statistical Machine Translation
... into language models in several ...decomposition based on a segmented training corpus. They es- timate unigram topic-based probability and com- bine it with standard n-gram ...topic model for ... See full document
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Unsupervised Adaptation for Statistical Machine Translation
... LM adaptation for ...TM adaptation. (Hildebrand et al., 2005) perform LM and TM adaptation based on infor- mation retrieval ...source- language test corpus to filter the bilingual data, ... See full document
9
A Sense Based Translation Model for Statistical Machine Translation
... the translation of the word. In this paper, we propose a sense-based transla- tion model to integrate word senses into statistical machine ...tagger based on a nonparametric ... See full document
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Maximum Entropy based Rule Selection Model for Syntax based Statistical Machine Translation
... for non-ambiguous source tree will be set to 1.0. Therefore, the decoder will prefer to use non-ambiguous TATs. However, non- ambiguous TATs usually occur only once in the training corpus, which are not reliable. Thus we ... See full document
9
Translation Model Based Cross Lingual Language Model Adaptation: from Word Models to Phrase Models
... LSA model for LM ...marginal adaptation which minimizes the Kullback- Leibler divergence between the adapted LM and the generic ...two cross-lingual ap- proaches focus on modify LM itself, which are ... See full document
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Language Model Adaptation for Statistical Machine Translation via Structured Query Models
... contains translation candidates, and thus is more informative than Q T 1 ...query model. 2.2.3 Translation Model as a Query Model To fully leverage the available knowledge from the ... See full document
7
Context Adaptation in Statistical Machine Translation Using Models with Exponentially Decaying Cache
... Cache based adapta- tion can directly be applied to any new domain and similar gains should be ...cache model on the entire text in a second ...the translation costs assigned by the ... See full document
8
Maximum Entropy Based Phrase Reordering Model for Statistical Machine Translation
... the language model (NONE) we get the worst performance, even worse than the monotone ...our language models were not strong to discriminate between straight orders and inverted ...the language ... See full document
8
Phrase Reordering Model Integrating Syntactic Knowledge for SMT
... reordering model in SMT systems, ranging from the fundamental distance-based dis- tortion model (Och and Ney, 2004; Koehn et ...reordering model (Wu, 1996; Zens et ...reordering model ... See full document
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