Paper Accepted at ICBSLP 2019
Our paper “Neural vs Statistical Machine Translation: Revisiting the Bangla-English Language Pair” accepted at ICCIT 2018. Congratulations authors: Md. Arid Hasan, Firoj Alam, Shammur Absar Chowdhury, and Naira Khan. Another contribution that can enrich Bangla language computing research.
Please follow us on researchgate to keep up updated.
Abstract
Machine translation systems facilitate our communication and access to information, taking down language barriers. It is a well-researched area of Natural Language Processing(NLP), especially for resource-rich languages (e.g., language pairs in Europarl Parallel corpus). Besides these languages, there is also work on other language pairs including the Bangla-English language pair. In the current study, we aim to revisit both Statistical Machine Translation (SMT) and Neural Machine Translation (NMT) approaches using well-known, publicly avail-able corpora for the Bangla-English (Bangla to English) language pair. We reported how the performance of the models differ based on the data and modeling techniques; consequently, we also compared the results obtained with Google’s machine translation system. Our findings, across different corpora, indicates that NMT based approaches outperform SMT systems. Our results also outperform existing baselines by a large margin.
Paper Link and BibTeX
Paper Link
We will update soon…
Bib
@inproceedings{hasan2019neural,
title={Neural vs Statistical Machine Translation: Revisiting the Bangla-English Language Pair},
author={Hasan, Md. Arid and Alam, Firoj and Chowdhury, Shammur Absar and Khan, Naira},
booktitle={2019 2nd International Conference of Bangla Speech and Language Processing (ICBSLP)},
year={2019},
organization={IEEE}
}