Improving Mandarin Prosodic Structure Prediction with Multi-level Contextual Information

• URL: http://arxiv.org/abs/2308.16577v1
• Date: Thu, 31 Aug 2023 09:19:15 GMT
• Title: Improving Mandarin Prosodic Structure Prediction with Multi-level Contextual Information
• Authors: Jie Chen, Changhe Song, Deyi Tuo, Xixin Wu, Shiyin Kang, Zhiyong Wu, Helen Meng
• Abstract summary: This work proposes to use inter-utterance linguistic information to improve the performance of prosodic structure prediction (PSP) Our method achieves better F1 scores in predicting prosodic word (PW), prosodic phrase (PPH) and intonational phrase (IPH)
• Score: 68.89000132126536
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: For text-to-speech (TTS) synthesis, prosodic structure prediction (PSP) plays an important role in producing natural and intelligible speech. Although inter-utterance linguistic information can influence the speech interpretation of the target utterance, previous works on PSP mainly focus on utilizing intrautterance linguistic information of the current utterance only. This work proposes to use inter-utterance linguistic information to improve the performance of PSP. Multi-level contextual information, which includes both inter-utterance and intrautterance linguistic information, is extracted by a hierarchical encoder from character level, utterance level and discourse level of the input text. Then a multi-task learning (MTL) decoder predicts prosodic boundaries from multi-level contextual information. Objective evaluation results on two datasets show that our method achieves better F1 scores in predicting prosodic word (PW), prosodic phrase (PPH) and intonational phrase (IPH). It demonstrates the effectiveness of using multi-level contextual information for PSP. Subjective preference tests also indicate the naturalness of synthesized speeches are improved.

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