CantonMT: Cantonese to English NMT Platform with Fine-Tuned Models Using Synthetic Back-Translation Data

Kung Yin Hong, Lifeng Han, Riza Batista-Navarro, Goran Nenadic
3/17/2024
cs.CLcs.AI

Official code: kenrickkung/CantoneseTranslation (4 stars, last commit 2024-03-20).

Abstract

Neural Machine Translation (NMT) for low-resource languages is still a challenging task in front of NLP researchers. In this work, we deploy a standard data augmentation methodology by back-translation to a new language translation direction Cantonese-to-English. We present the models we fine-tuned using the limited amount of real data and the synthetic data we generated using back-translation including OpusMT, NLLB, and mBART. We carried out automatic evaluation using a range of different metrics including lexical-based and embedding-based. Furthermore. we create a user-friendly interface for the models we included in this\textsc{ CantonMT} research project and make it available to facilitate Cantonese-to-English MT research. Researchers can add more models into this platform via our open-source\textsc{ CantonMT} toolkit \url{https://github.com/kenrickkung/CantoneseTranslation}.

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kenrickkung/CantoneseTranslationOfficial100%

Third Year Project for Bsc Computer Science in University of Manchester

41R, CSSOct 10, 20232 years ago

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Cite this paper

@article{hong2024cantonmt,
  title  = {CantonMT: Cantonese to English NMT Platform with Fine-Tuned Models Using Synthetic Back-Translation Data},
  author = {Kung Yin Hong and Lifeng Han and Riza Batista-Navarro and Goran Nenadic},
  year   = {2024},
  eprint = {2403.11346},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.11346v3}
}

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