[PDF] Top 20 Unsupervised Adaptation for Statistical Machine Translation
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Unsupervised Adaptation for Statistical Machine Translation
... and translation models domain- adaptation without explicit bilingual in- domain training ...explore unsupervised adaptation, where the source-language test corpus is combined with the ... See full document
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Perplexity Minimization for Translation Model Domain Adaptation in Statistical Machine Translation
... multiple translation mod- els as alternative decoding paths (Birch et ...final translation. In practice, each translation model adds 5 features and thus 5 more dimensions to the weight space, which ... See full document
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Unsupervised Domain Adaptation for Neural Machine Translation with Domain Aware Feature Embeddings
... Baselines. We compare our methods with two baseline models: 1) The copied monolingual data model (Currey et al., 2017) which copies tar- get in-domain monolingual data to the source side; 2) Back-translation ... See full document
6
Translation Model Adaptation for Statistical Machine Translation with Monolingual Topic Information
... topic-dependent translation lexicons in the training process, we estimate topic-specific lexical probability by taking account of topical context when extract- ing word pairs, so our method can also be di- rectly ... See full document
10
NICT’s Unsupervised Neural and Statistical Machine Translation Systems for the WMT19 News Translation Task
... using unsupervised Vecmap (Artetxe et ...backward translation systems, instead of using only either forward (Marie and Fujita, 2018b) or backward translations (Artetxe et ... See full document
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Phrase Training Based Adaptation for Statistical Machine Translation
... The standard phrase extraction procedure in SMT consists of two phases: (i) word-alignment training (e.g., IBM alignment models), (ii) heuristic phrase extraction and relative frequency based phrase trans- lation ... See full document
6
Continuous Adaptation to User Feedback for Statistical Machine Translation
... the adaptation perfor- ...project adaptation scheme which take advantage of continuous space language modeling (CSLM) as explained in section ...that adaptation in such an ap- proach is ... See full document
5
Domain Adaptation for Statistical Machine Translation with Domain Dictionary and Monolingual Corpora
... Statistical machine translation systems are usually trained on large amounts of bilingual text and monolingual ...domain adaptation for statistical machine translation, ... See full document
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Unsupervised Tokenization for Machine Translation
... Tokenizing a parallel corpus is usually the first step of training a statistical machine translation system. With languages such as Chinese, which has no spaces in its writing system, the main chal- ... See full document
9
Language and Translation Model Adaptation using Comparable Corpora
... Traditionally, statistical machine translation systems have relied on parallel bi-lingual data to train a translation ...a statistical machine translation system on news ... See full document
10
Context Adaptation in Statistical Machine Translation Using Models with Exponentially Decaying Cache
... on translation quality. Using our hy- pothesis of translation consistency we expected another gain on our test ...cache translation op- tions for which the transition costs (of adding this option to ... See full document
8
Unsupervised Alignment for Segmental based Language Understanding
... Statistical alignment methods used in machine translation are relevant in our context if we consider that the target language is the concept language. There are nevertheless differences with genuine ... See full document
8
Discriminative Instance Weighting for Domain Adaptation in Statistical Machine Translation
... Domain adaptation is a common concern when op- timizing empirical NLP ...of Statistical Machine Translation (SMT) systems, an additional complication is the heterogeneous na- ture of SMT ... See full document
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Connecting Phrase based Statistical Machine Translation Adaptation
... 1998) adaptation (pruning), (Duh et ...sentence adaptation, (Sennrich, 2012) for TM weights combination, and (Bisazza et ...based adaptation directly for all phrases, and ‘in+connect’ indicates ... See full document
11
A Post editing Interface for Immediate Adaptation in Statistical Machine Translation
... Technical translation effort is approximated by HBLEU+1 and HTER, comparing MT outputs to post-edits, and time is normalized by the number of characters in the final ...the translation condition ... See full document
5
Hybrid Adaptation of Named Entity Recognition for Statistical Machine Translation
... Second, we looked at the NE density in the corpus and how the integration of the prediction model impacts it. Table 3 reports the number of different NEs (by type) detected in total in each test set, and the number of ... See full document
16
Hierarchical Incremental Adaptation for Statistical Machine Translation
... incremental adaptation ap- proach for statistical machine translation that maintains a flexible hierarchical do- main structure within a single consistent ...in translation quality from ... See full document
7
Integrating an Unsupervised Transliteration Model into Statistical Machine Translation
... the unsupervised transliteration mining system, which automatically mines transliteration pairs from the same word-aligned parallel corpus as used for training the MT ... See full document
6
Unsupervised Search for the Optimal Segmentation for Statistical Machine Translation
... completely unsupervised since it requires external linguistic resources in initializing the segmentation with the output of a morphological analyzer and disam- ... See full document
6
Adaptation of Reordering Models for Statistical Machine Translation
... “verb adverb” order in that language as well. Figure 2 shows how a different word order in the Mandarin source affects reordering when translating into En- glish. Perhaps in situations where different training corpora ... See full document
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