[PDF] Top 20 Guiding Statistical Word Alignment Models With Prior Knowledge
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Guiding Statistical Word Alignment Models With Prior Knowledge
... incorporate prior knowledge such as heuristics or linguistic features into statistical generative word alignment ...models. Prior knowledge serves as soft ... See full document
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Extentions to HMM based Statistical Word Alignment Models
... tential of part of speech information to better model translation probabilities and permutation probabili- ties. Melamed (2000) uses a very broad classifica- tion of words (content, function and several punctu- ation ... See full document
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Smaller Alignment Models for Better Translations: Unsupervised Word Alignment with the l0 norm
... the word-to- word translation table, reducing overfitting, and, in particular, the “garbage collection” ...this prior efficiently, even for large ...better statistical translation ... See full document
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A Systematic Comparison of Various Statistical Alignment Models
... the alignment quality of statistical methods when linguistic knowledge is used (Ker and Chang 1997; Huang and Choi ...linguistic knowledge is used mainly to filter out incorrect align- ...the ... See full document
33
Bayesian Word Alignment for Statistical Machine Translation
... the alignment probabilities are inferred by integrating over all possible parameter values as- suming an intuitive, sparse ...order alignment models, and (2) many state-of-the- art SMT systems use ... See full document
6
BiTAM: Bilingual Topic AdMixture Models for Word Alignment
... translation models concern mainly explicit logical representations of semantics for machine ...include knowledge-based (Nyberg and Mitamura, 1992) and interlingua-based (Dorr and Habash, 2002) ...using ... See full document
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Learning Tractable Word Alignment Models with Complex Constraints
... HMM word alignment model (Vogel, Ney, and Tillmann 1996), using a novel unsupervised learning framework that significantly boosts its ...incorporates prior knowledge in the form of constraints ... See full document
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Simpler Is Better: Re-evaluation of Default Word Alignment Models in Statistical MT
... IBM models, as proposed by (Och and Ney, 2003), is IBM model 1, HMM-based model, IBM model 3 and finally model 4, whereas the resulting parameters of the simpler models are used as the initial values of the ... See full document
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Semi Supervised Training for Statistical Word Alignment
... use word-level translation tables informed by both the “E to F” and the “F to E” translation directions derived us- ing the three symmetrization heuristics, the “E to F” translation table from the final iteration ... See full document
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Multi Word Expression Sensitive Word Alignment
... new word align- ment method which incorporates knowl- edge about Bilingual Multi-Word Expres- sions ...of word alignment first extracts such BMWEs in a bidirectional way for a given corpus and ... See full document
9
Extracting Parallel Phrases from Comparable Data
... including word transla- tion pairs, named entities, and long phrase ...ment models. Kumano et al. (2007) have proposed a phrasal alignment approach for comparable corpora using the joint probability ... See full document
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Simultaneous Word Morpheme Alignment for Statistical Machine Translation
... Current word alignment models for statisti- cal machine translation do not address mor- phology beyond merely splitting ...two-level alignment model that dis- tinguishes between words and ... See full document
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Improved Alignment Models for Statistical Machine Translation
... The results of the translation experiments using the single-word based approach and the alignment template approach on text input and on speech input are summarized in Table 2.. The resu[r] ... See full document
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A Comparison of Alignment Models for Statistical Machine Translation
... paper dvi A Comparison of Alignment Models for Statistical Machine Translation Franz Josef Och and Hermann Ney Lehrstuhl f?ur Informatik VI, Computer Science Department RWTH Aachen University of Techn[.] ... See full document
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Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions
... 866 Word Alignment for Languages with Scarce Resources Using Bilingual Corpora of Other Language Pairs Haifeng Wang, Hua Wu and Zhanyi Liu.. 874 Combining Statistical and Knowledge-Based[r] ... See full document
10
Temperature Driven Anomaly Detection Methods for Structural Health Monitoring
... 21 For the purpose of data pattern recognition, generally, researchers are using a certain reference period data obtained from health structure to construct a statistical model to represent the structure’s normal ... See full document
235
Learning Word Representations with Regularization from Prior Knowledge
... ternal knowledge has to be clustered beforehand according to their semantic relatedness ...precise word-word relations is ...as knowledge that is learned else- where, such as from topic ... See full document
10
Boosting Statistical Word Alignment Using Labeled and Unlabeled Data
... This method only uses the labeled data as train- ing data. According to the algorithm in figure 1, we obtain and . Thus, we only change the distribution of the labeled data. How- ever, we build an unsupervised model ... See full document
8
Multiple Word Alignment with Profile Hidden Markov Models
... alignment (Durbin et al., 1998). In this paper, we show that Profile HMMs can be adapted to the task of aligning multiple words. We apply them to sets of multilingual cognates and show that they pro- duce good ... See full document
6
HMM Word and Phrase Alignment for Statistical Machine Translation
... source word fertility, and the distortion model. The WtoP alignment model includes the first two of ...(Markov) alignment process as well as by the phrase count ...WtoP alignment model and ... See full document
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