UCSMNLP: Statistical Machine Translation for WAT 2019
This paper represents UCSMNLP{'}s submission to the WAT 2019 Translation Tasks focusing on the Myanmar-English translation. Phrase based statistical machine translation (PBSMT) system is built by using other resources: Name Entity Recognition (NER) corpus and bilingual dictionary which is created by Google Translate (GT). This system is also adopted with listwise reranking process in order to improve the quality of translation and tuning is done by changing initial distortion weight. The experimental results show that PBSMT using other resources with initial distortion weight (0.4) and listwise reranking function outperforms the baseline system.
Code (0)
등록된 구현이 없습니다.
Tasks
Machine TranslationNERRerankingTranslationSimilar Papers 제목 키워드 기반
Improving the Performance of English-Tamil Statistical Machine Translation System using Source-Side Pre-Processing
Machine Translation is one of the major oldest and the most active research area in Natural Language Processing. Currently, Statistical Machine Translation (SMT) dominates the Machine Translation research. Statistical Ma…
Machine TranslationSentenceTranslationA Hybrid Model for Enhancing Lexical Statistical Machine Translation (SMT)
The interest in statistical machine translation systems increases currently due to political and social events in the world. A proposed Statistical Machine Translation (SMT) based model that can be used to translate a se…
Language ModelingLanguage ModellingMachine TranslationSentence+1Extended Parallel Corpus for Amharic-English Machine Translation
This paper describes the acquisition, preprocessing, segmentation, and alignment of an Amharic-English parallel corpus. It will be helpful for machine translation of a low-resource language, Amharic. We freely released t…
Language ModelingLanguage ModellingMachine TranslationTranslationImproving Statistical Machine Translation with Selectional Preferences
Long-distance semantic dependencies are crucial for lexical choice in statistical machine translation. In this paper, we study semantic dependencies between verbs and their arguments by modeling selectional preferences i…
Machine TranslationSemantic Role LabelingTranslationWord Sense DisambiguationStudy on Unsupervised Statistical Machine Translation for Backtranslation
Machine Translation systems have drastically improved over the years for several language pairs. Monolingual data is often used to generate synthetic sentences to augment the training data which has shown to improve the …
Machine TranslationTranslationUnsupervised Machine Translation