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2020 AACL AACL 2020

EnAsCorp1.0: English-Assamese Corpus

Abstract

AbstractThe corpus preparation is one of the important challenging task for the domain of machine translation especially in low resource language scenarios. Country like India where multiple languages exists, machine translation attempts to minimize the communication gap among people with different linguistic backgrounds. Although Google Translation covers automatic translation of various languages all over the world but it lags in some languages including Assamese. In this paper, we have developed EnAsCorp1.0, corpus of English-Assamese low resource pair where parallel and monolingual data are collected from various online sources. We have also implemented baseline systems with statistical machine translation and neural machine translation approaches for the same corpus.

🚀 Conference Pioneer — AACL 2020
🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio

Authors

Sahinur Rahman Laskar , Abdullah Faiz Ur Rahman Khilji , Partha Pakray , Sivaji Bandyopadhyay

Topics

Artificial Intelligence > Learning Paradigms > Transfer Learning Natural Language Processing > Applications > Machine Translation Natural Language Processing > Resources & Methods > Multilingual NLP Machine Learning > Learning Paradigms > Transfer Learning

Keywords

machine translation neural machine translation parallel corpus statistical machine translation low-resource language low resource language
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