How do different tokenizers perform on downstream tasks in scriptio continua languages?: A case study in Japanese (2023.acl-srw)
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| Challenge: | Existing studies on scriptio continua languages lack comprehensiveness of tokenizers . authors use Byte-Pair-Encoding or Unigram instead of WordPiece for subword tokenizer . |
| Approach: | They investigate the effect of tokenizers on the downstream performance of pretrained language models in scriptio continua languages where no explicit spaces exist between words. |
| Outcome: | The proposed tokenizers perform better on a wide range of tasks compared with other tokenizer methods . the results show that each task has an optimal morphological analyzer . |
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