Journal of Information Processing Systems

  • 제17권1호
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  • Pages.203-212
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  • 2021
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  • 1976-913X(pISSN)
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  • 2092-805X(eISSN)
한국정보처리학회 (Korea Information Processing Society)
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Optimized Chinese Pronunciation Prediction by Component-Based Statistical Machine Translation

  • Zhu, Shunle (Donghai Science and Technology College, Zhejiang Ocean University)
  • 투고 : 2018.08.31
  • 심사 : 2019.05.29
  • 발행 : 2021.02.28
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초록

To eliminate ambiguities in the existing methods to simplify Chinese pronunciation learning, we propose a model that can predict the pronunciation of Chinese characters automatically. The proposed model relies on a statistical machine translation (SMT) framework. In particular, we consider the components of Chinese characters as the basic unit and consider the pronunciation prediction as a machine translation procedure (the component sequence as a source sentence, the pronunciation, pinyin, as a target sentence). In addition to traditional features such as the bidirectional word translation and the n-gram language model, we also implement a component similarity feature to overcome some typos during practical use. We incorporate these features into a log-linear model. The experimental results show that our approach significantly outperforms other baseline models.

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참고문헌

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