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

• URL: http://arxiv.org/abs/2403.11346v3
• Date: Sun, 9 Jun 2024 22:10:04 GMT
• Title: CantonMT: Cantonese to English NMT Platform with Fine-Tuned Models Using Synthetic Back-Translation Data
• Authors: Kung Yin Hong, Lifeng Han, Riza Batista-Navarro, Goran Nenadic,
• Abstract summary: This work deploys 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 create a user-friendly interface for the models we included in thistextsc CantonMT research project and make it available to facilitate Cantonese-to-English MT research.
• Score: 9.244878233604819
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• 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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