Raj Dabre

A Brief Survey of Multilingual Neural Machine Translation

2019 · arXiv (Cornell University)

We present a survey on multilingual neural machine translation (MNMT), which has gained a lot of traction in the recent years. MNMT has been useful in improving translation quality as a result of knowledge transfer. …

YANMTT: Yet Another Neural Machine Translation Toolkit

2021 · arXiv (Cornell University)

In this paper we present our open-source neural machine translation (NMT) toolkit called "Yet Another Neural Machine Translation Toolkit" abbreviated as YANMTT which is built on top of the Transformers library. Despite the growing importance …

MorisienMT: A Dataset for Mauritian Creole Machine Translation

2022 · arXiv (Cornell University)

In this paper, we describe MorisienMT, a dataset for benchmarking machine translation quality of Mauritian Creole. Mauritian Creole (Morisien) is the lingua franca of the Republic of Mauritius and is a French-based creole language. MorisienMT …

RomanSetu: Efficiently unlocking multilingual capabilities of Large Language Models via Romanization

2024 · arXiv (Cornell University)

This study addresses the challenge of extending Large Language Models (LLMs) to non-English languages that use non-Roman scripts. We propose an approach that utilizes the romanized form of text as an interface for LLMs, hypothesizing …

A Multilingual Multiway Evaluation Data Set for Structured Document Translation of Asian Languages

2022

Translation of structured content is an important application of machine translation, but the scarcity of evaluation data sets, especially for Asian languages, limits progress.In this paper we present a novel multilingual multiway evaluation data set …

An Empirical Comparison of Simple Domain Adaptation Methods for Neural Machine Translation

2017 · arXiv (Cornell University)

In this paper, we propose a novel domain adaptation method named "mixed fine tuning" for neural machine translation (NMT). We combine two existing approaches namely fine tuning and multi domain NMT. We first train an …

An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation

2017

In this paper, we propose a novel domain adaptation method named "mixed fine tuning" for neural machine translation (NMT). We combine two existing approaches namely fine tuning and multi domain NMT. We first train an …

Overview of the 8th Workshop on Asian Translation

2021

Toshiaki Nakazawa, Hideki Nakayama, Chenchen Ding, Raj Dabre, Shohei Higashiyama, Hideya Mino, Isao Goto, Win Pa Pa, Anoop Kunchukuttan, Shantipriya Parida, Ondřej Bojar, Chenhui Chu, Akiko Eriguchi, Kaori Abe, Yusuke Oda, Sadao Kurohashi. Proceedings of …

Overview of the 7th Workshop on Asian Translation

2020

Toshiaki Nakazawa, Hideki Nakayama, Chenchen Ding, Raj Dabre, Shohei Higashiyama, Hideya Mino, Isao Goto, Win Pa Pa, Anoop Kunchukuttan, Shantipriya Parida, Ondřej Bojar, Sadao Kurohashi. Proceedings of the 7th Workshop on Asian Translation. 2020.