Bilingually-constrained Phrase Embeddings for Machine Translation
Code (0)
등록된 구현이 없습니다.
Tasks
Language ModellingMachine TranslationSemantic Textual SimilarityTranslationWord AlignmentWord EmbeddingsSimilar Papers 제목 키워드 기반
Local Translation Prediction with Global Sentence Representation
Statistical machine translation models have made great progress in improving the translation quality. However, the existing models predict the target translation with only the source- and target-side local context inform…
Machine TranslationPredictionSentenceTranslationBilingual Low-Resource Neural Machine Translation with Round-Tripping: The Case of Persian-Spanish
The quality of Neural Machine Translation (NMT), as a data-driven approach, massively depends on quantity, quality, and relevance of the training dataset. Such approaches have achieved promising results for bilingually h…
Low Resource Neural Machine TranslationLow-Resource Neural Machine TranslationLow Resource NMTMachine Translation+2Phrase-based Unsupervised Machine Translation with Compositional Phrase Embeddings
This paper describes the University of Tartu{'}s submission to the unsupervised machine translation track of WMT18 news translation shared task. We build several baseline translation systems for both directions of the En…
Machine TranslationTranslationUnsupervised Machine TranslationLearning to Generate Word- and Phrase-Embeddings for Efficient Phrase-Based Neural Machine Translation
Neural machine translation (NMT) often fails in one-to-many translation, e.g., in the translation of multi-word expressions, compounds, and collocations. To improve the translation of phrases, phrase-based NMT systems ha…
DecoderMachine TranslationNMTTranslationAn Effective Optimization Method for Neural Machine Translation: The Case of English-Persian Bilingually Low-Resource Scenario
In this paper, we propose a useful optimization method for low-resource Neural Machine Translation (NMT) by investigating the effectiveness of multiple neural network optimization algorithms. Our results confirm that app…
Low Resource Neural Machine TranslationLow-Resource Neural Machine TranslationMachine TranslationNMT+1