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Extending the Subwording Model of Multilingual Pretrained Models for New Languages

2022-11-29 06:55:34
Kenji Imamura, Eiichiro Sumita
arXiv_CL
   
Abstract

Multilingual pretrained models are effective for machine translation and cross-lingual processing because they contain multiple languages in one model. However, they are pretrained after their tokenizers are fixed; therefore it is difficult to change the vocabulary after pretraining. When we extend the pretrained models to new languages, we must modify the tokenizers simultaneously. In this paper, we add new subwords to the SentencePiece tokenizer to apply a multilingual pretrained model to new languages (Inuktitut in this paper). In our experiments, we segmented Inuktitut sentences into subwords without changing the segmentation of already pretrained languages, and applied the mBART-50 pretrained model to English-Inuktitut translation.

Abstract (translated)

URL

https://arxiv.org/abs/2211.15965

PDF

https://arxiv.org/pdf/2211.15965.pdf

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