[PDF] Top 20 Discriminative Instance Weighting for Domain Adaptation in Statistical Machine Translation

... Finally, we make some improvements to baseline approaches. We train linear mixture models for con- ditional phrase pair probabilities over IN and OUT so as to maximize the likelihood of an empirical joint phrase-pair ... See full document

... Statistical machine translation systems are usually trained on large amounts of bilingual text and monolingual ...form domain adaptation for statistical machine ... See full document

... Domain adaptation has recently gained interest in statistical machine translation to cope with the performance drop ob- served when testing conditions deviate from training ...data. ... See full document

... 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 translation ... See full document

... the domain of medical texts ...specific domain tuning by analysing the results in detail. In a nutshell: domain tuning for matching-domain training, tuning and test data results in feature ... See full document

... In the remainder of this paper, we first review previous work in Section 2, highlighting the main weaknesses of existing methods for inducing a phrase table for domain adaptation, and our moti- vation. In ... See full document

... the translation quality. Although we added the ASPEC corpus as a fifth domain, the effects were not ...Our domain adaptation can incorporate external knowledge, such as Google n-gram language ... See full document

... contrast, weighting the translation models (weighted TM mode) leads to a significant im- provement of all scores in both language pairs (all at p ≤ ...out-of-domain translation models is a ... See full document

... Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexandra Constantin, and Evan ... See full document

... new domain adaptation technique for neural machine translation called cost weighting, which is appropriate for adaptation scenarios in which a small in-domain data set and ... See full document

... the domain in which the system will operate using a mixture model ...approach. Domain adaptation of translation mod- els (TMs) and language models (LMs) has become common for SMT systems, but ... See full document

... and translation models domain- adaptation without explicit bilingual in- domain training ...the domain can be induced from the source-language test ...unsupervised adaptation, ... See full document

... Another popular task in SMT is domain adapta- tion (Foster et al., 2010). It tries to take advantage of any out-of-domain training data by combining them with the in-domain data in an appropriate ... See full document

... Discriminative lexicons address some of the core challenges of phrase-based MT (PBMT) when translating to morphologically rich languages, such as Czech, namely sense disambiguation and morphological coherence. The ... See full document

... But MT is not just an object of academic study. It’s a real application that isn’t fully perfected, and the best way to learn about it is to build an MT sys- tem. This can be done with open-source toolkits such as Moses ... See full document

... In machine translation, intuitively, the informative content words should be emphasized more for better adequacy of the translation ...tical translation approach does not take account how ... See full document

... the Machine Learning ...on Machine Learning (2016), Best Paper Award at the International Conference on Learning Representations (2016), Winner of round 5 of the Yelp Dataset Challenge (2015), Distinguished ... See full document

... As specific MT method, we use the alignment tem- plate approach (Och et al., 1999). The key elements of this approach are the alignment templates, which are pairs of source and target language phrases to- gether with an ... See full document

... Our weight adaptation is performed using a hier- archical extension to fast and adaptive online train- ing (Green et al., 2013b), a technique based on Ada- Grad (Duchi et al., 2011) and forward-backward splitting ... See full document

... out-of- domain data and then select data that are similar to in-domain text based on the resulting scores, a paradigm adapted by Duh et ...perform adaptation for NMT by re- trieving sentences or ... See full document