[PDF] Top 20 Improving Statistical Machine Translation with Selectional Preferences

... Selectional preferences place semantic restrictions on words, with which words can co-occur in dif- ferent syntactic ...object preferences for the verb “drink” are ...alleviate translation ... See full document

... In this way, the system can differentiate the distor- tion distributions for single source words with differ- ent POS tags, such as adjectives versus nouns. And in the meantime, we also differentiate the distortion ... See full document

... for translation of PVs, we limit the construction of phrases in the training data for word2vec only to those English and Bul- garian phrases which: i) are aligned in the phrase table and ii) the English phrase ... See full document

... Neural Machine Translation (NMT) model generates trans- lations from left to right as a linear sequence, during which latent syntactic structures of the target sentences are not explicitly ...for ... See full document

... current statistical MT models, especially the growing family of tree- structured SMT models employing stochastic trans- duction grammars of various sorts (Wu and Chiang, ...structured statistical MT model ... See full document

... the translation model is treated as the monotonic backbone of the search space, while the language model score is a non-monotonic cost that distorts the search space (see (Huang and Chiang, 2005) for defini- tion ... See full document

... a translation model P r(e|f ) and a target language model P r(e), which can be complemented by reordering models (if the language pairs presents very long alignments in training), word penalty to avoid favoring ... See full document

... French translation; Collins et ...German-to-English translation; Li et ...English translation, which reversed the word order in Japanese segments separated by a few simple cues; Xu et ...or ... See full document

... Table 4. Offline data optimization results 4.4 Online model optimization experiments Since 2005 NIST MT test data tends bias to FBIS corpus too much, we build a new test set to evalu- ate the online model optimization ... See full document

... where X denotes any phrase. Because “X 了” wrongly written as “了 X” is a typical Disorder error in Chinese sentences, the hierarchical phrase-based system extracts the rule X→(X 了, 了 X) and weighs it highly when training ... See full document

... pivot translation system, and then each pivot sen- tence is translated to m target sentences via a piv- ot-target translation ...multiple translation outputs will be generated, thus a minimum Bayes- ... See full document

... based translation system performs better on word alignment than the translation dictionary?” For single word alignment, the rule-based translation system can perform word sense disambiguation, and ... See full document

... Improving Statistical Machine Translation Using Word Sense Disambiguation Marine Carpuat and Dekai Wu.. Large Margin Synchronous Generation and its Application to Sentence Compression Tr[r] ... See full document

... its statistical rather then any gram- matical ...a translation of the ...a translation. These operations are determined by statistical properties of the target lan- guage enshrined in the ... See full document

... To investigate the effectiveness of the method proposed in section 4, we only use the colloca- tion model CM-3 as described in section 5.1. The results are shown in Table 5. When the phrase collocation probabilities are ... See full document

... Alexandrescu and Kirchhoff (2009) use a graph-based semi-supervised model determine similarities between sentences, then use it to re- rank the n-best translation hypothesis. Liu et al. (2012) extend this model to ... See full document

... engine, machine Task operation, test, study, analysis, duty Arrangement agreement, policy, term, rule, procedure Matter aspect, subject, issue, question, case Problem difficulty, challenge, loss, pressure, fear ... See full document

... An analysis of the judgements on the remain- ing three evaluation criteria (outlined in Section 4.4) for the 31 differences provides further infor- mation. The Baseline system appears to be more accurate, with 19 ... See full document

... Pseudo-words were introduced simultaneously by two papers studying statistical approaches to word sense disambiguation (WSD). Sch¨utze (1992) simply called the words, ‘artificial ambiguous words’, but Gale et al. ... See full document

... the translation and language models can further improve the translation ...a translation model trained on a concatenation of S → T and T → S parallel corpora and a language model compiled from a ... See full document