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John Richardson - 2015 - KyotoEBMT System Description for the 2nd Workshop on Asian Translation
1.
KyotoEBMT)System)Descrip3on)for)the)2nd)Workshop)on)Asian)Transla3on John Richardson Raj
Dabre Chenhui Chu Fabien Cromières Toshiaki Nakazawa Sadao Kurohashi Graduate School of Informatics, Kyoto University Language Knowledge Engineering Lab. Kyoto University nakazawa@pa.jst.jpjohn@nlp.ist.i.kyoto-u.ac.jp fabien@pa.jst.jp kuro@i.kyoto-u.ac.jp Illustration of Translation Process KyotoEBMT System Pipeline [Cromieres)and)Kurohashi,)EMNLP)2014] Web Interface of Translation Translation with Lattice Rules • designed)to)handle)an)arbitrary)number)of)nonA terminals) • able)to)handle)ambiguiBes)of)translaBon) hypotheses) ! which)target)word)is)going)to)be)used) ! which)will)be)the)final)posiBon)of)each)nonAterminal WAT2015 Official Results Rerank BLEU RIBES HUMAN JE NO 21.31)(+0.71) 70.65)(+0.53) 16.50 YES 22.89)(+1.82) 72.46)(+2.56) 32.50 EJ NO) 30.69)(+0.92) 76.78)(+1.57) 40.50 YES 33.06)(+1.97) 78.95)(+2.99) 51.00 JC NO 29.99)(+2.78) 80.71)(+1.58) 16.00 YES 31.40)(+3.83) 82.70)(+3.87) 12.50 CJ NO 36.30)(+2.73) 81.97)(+1.87) 16.75 YES 38.53)(+3.78) 84.07)(+3.81) 18.50 Dependency)Parsers) )))))Ja:)KNP)[Kawahara)and)Kurohashi,)2006]) )))))En:)NLParser)[Charniak)and)Johnson,)2005])with)rules) )))))Zh:)SKP)[Shen)et)al.,)2012]) Reranking)Features) )))))7Agram)language)model)with)Modified)KneserANey)smoothing) )))))Recurrent)Neural)Network)Language)Model)(hidden)layer:)200))(Mikolov,)2011)) )))))Bilingual)RNN)Language)Model)(Bahdanau)et)al.,)2015) Each)path)in)this)laYce)corresponds)to)different)choices)of) inserBon)posiBon)for)X2,)morphological)forms)of)“be”,)and) the)opBonal)inserBon)of)“at”. Conclusion and Future Work KyotoEBMT)system) )))))A)source)code)available)under)a)GPL)license)at)) )))))))))))))))))))))))))h_p://nlp.ist.i.kyotoAu.ac.jp/kyotoebmt/) ))))))))))))))(version)1.0)just)released!)) )))))A)uses)both)source)and)target)dependency)analysis) )))))A)online)example)retrieving) )))))A)availability)of)full)translaBon)examples)at)run)Bme) )))))A)can)use)forest)parses)of)input) ) Future)work) )))))A)use)a)targetAside)tree)language)model) )))))A)online)tuning)of)weights) )))))A)targetAside)structural)features) )))))A)use)of)neural)network)language)models)in) decoding) ) (Improvement)over)WAT2014)in)parentheses)) Remark:)For)WAT2014,)JA>C)was)the)only)direcBon)for)which)reranking)was) worsening)BLEU)and)Human)EvaluaBon.)For)WAT2015,)JA>C)is)sBll)the)only) direcBon)for)which)reranking)worsens)Human)EvaluaBon)(although)it)now)does) improve)BLEU) dabre@nlp.ist.i.kyoto-u.ac.jp Fores t chu@pa.jst.jp
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