Shunle Zhu, Journal of Information Processing Systems Vol. 17, No. 1, pp. 203-212, Feb. 2021  

https://doi.org/10.3745/JIPS.04.0208
Keywords: Chinese Pronunciation Prediction, Component, Features, Statistical Machine Translation (SMT)
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Abstract

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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