Abstract
We demonstrate a program that learns to pronounce Chinese text in Mandarin, without a pronunciation dictionary. From non-parallel streams of Chinese characters and Chinese pinyin syllables, it establishes a many-to-many mapping between characters and pronunciations. Using unsupervised methods, the program effectively deciphers writing into speech. Its token-level character-to-syllable accuracy is 89%, which significantly exceeds the 22% accuracy of prior work.
Cite
CITATION STYLE
Chu, C., Fang, S., & Knight, K. (2020). Learning to pronounce Chinese without a pronunciation dictionary. In EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference (pp. 5687–5693). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2020.emnlp-main.458
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