2kenize: Tying Subword Sequences for Chinese Script Conversion

• URL: http://arxiv.org/abs/2005.03375v1
• Date: Thu, 7 May 2020 10:53:05 GMT
• Title: 2kenize: Tying Subword Sequences for Chinese Script Conversion
• Authors: Pranav A, Isabelle Augenstein
• Abstract summary: We propose a model that can disambiguate between mappings and convert between the two scripts. Our proposed method outperforms previous Chinese Character conversion approaches by 6 points in accuracy.
• Score: 54.33749520569979
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Simplified Chinese to Traditional Chinese character conversion is a common preprocessing step in Chinese NLP. Despite this, current approaches have poor performance because they do not take into account that a simplified Chinese character can correspond to multiple traditional characters. Here, we propose a model that can disambiguate between mappings and convert between the two scripts. The model is based on subword segmentation, two language models, as well as a method for mapping between subword sequences. We further construct benchmark datasets for topic classification and script conversion. Our proposed method outperforms previous Chinese Character conversion approaches by 6 points in accuracy. These results are further confirmed in a downstream application, where 2kenize is used to convert pretraining dataset for topic classification. An error analysis reveals that our method's particular strengths are in dealing with code-mixing and named entities.

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