Polyphone Disambiguation in Mandarin Chinese with Semi-Supervised Learning

• URL: http://arxiv.org/abs/2102.00621v3
• Date: Thu, 15 Aug 2024 06:51:57 GMT
• Title: Polyphone Disambiguation in Mandarin Chinese with Semi-Supervised Learning
• Authors: Yi Shi, Congyi Wang, Yu Chen, Bin Wang,
• Abstract summary: The majority of Chinese characters are monophonic, while a special group of characters, called polyphonic characters, have multiple pronunciations. As a prerequisite of performing speech-related generative tasks, the correct pronunciation must be identified among several candidates. We propose a novel semi-supervised learning framework for Mandarin Chinese polyphone disambiguation.
• Score: 9.13211149475579
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The majority of Chinese characters are monophonic, while a special group of characters, called polyphonic characters, have multiple pronunciations. As a prerequisite of performing speech-related generative tasks, the correct pronunciation must be identified among several candidates. This process is called Polyphone Disambiguation. Although the problem has been well explored with both knowledge-based and learning-based approaches, it remains challenging due to the lack of publicly available labeled datasets and the irregular nature of polyphone in Mandarin Chinese. In this paper, we propose a novel semi-supervised learning (SSL) framework for Mandarin Chinese polyphone disambiguation that can potentially leverage unlimited unlabeled text data. We explore the effect of various proxy labeling strategies including entropy-thresholding and lexicon-based labeling. Qualitative and quantitative experiments demonstrate that our method achieves state-of-the-art performance. In addition, we publish a novel dataset specifically for the polyphone disambiguation task to promote further research.

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