2019
EMNLP
EMNLP 2019
UCSMNLP: Statistical Machine Translation for WAT 2019
Abstract
AbstractThis 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.
🌉
Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
🧭
Keyword Pioneer
— listwise reranking
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Speech & Audio