Word Sense-Aware Machine Translation: Including Senses as Contextual Features for Improved Translation Models
Although it is commonly assumed that word sense disambiguation (WSD) should help to improve lexical choice and improve the quality of machine translation systems, how to successfully integrate word senses into such systems remains an unanswered question. Some successful approaches have involved reformulating either WSD or the word senses it produces, but work on using traditional word senses to improve machine translation have met with limited success. In this paper, we build upon previous work that experimented on including word senses as contextual features in maxent-based translation models. Training on a large, open-domain corpus (Europarl), we demonstrate that this aproach yields significant improvements in machine translation from English to Portuguese.
Code (0)
등록된 구현이 없습니다.
Tasks
Machine TranslationTranslationWord Sense DisambiguationSimilar Papers 제목 키워드 기반
Integrating Weakly Supervised Word Sense Disambiguation into Neural Machine Translation
This paper demonstrates that word sense disambiguation (WSD) can improve neural machine translation (NMT) by widening the source context considered when modeling the senses of potentially ambiguous words. We first introd…
ClusteringMachine TranslationNMTTranslation+1Expanding wordnets to new languages with multilingual sense disambiguation
Princeton WordNet is one of the most important resources for natural language processing, but is only available for English. While it has been translated using the expand approach to many other languages, this is an expe…
Information RetrievalMachine TranslationSentiment AnalysisTranslation+1Handling Homographs in Neural Machine Translation
Homographs, words with different meanings but the same surface form, have long caused difficulty for machine translation systems, as it is difficult to select the correct translation based on the context. However, with t…
Machine TranslationNMTTranslationWord Embeddings+1Polylingual Wordnet
Princeton WordNet is one of the most important resources for natural language processing, but is only available for English. While it has been translated using the expand approach to many other languages, this is an expe…
Machine TranslationTranslationWord Sense DisambiguationUsing Linked Disambiguated Distributional Networks for Word Sense Disambiguation
We introduce a new method for unsupervised knowledge-based word sense disambiguation (WSD) based on a resource that links two types of sense-aware lexical networks: one is induced from a corpus using distributional seman…
Machine TranslationTranslationWord EmbeddingsWord Sense Disambiguation