基于Hearer模型的中国TTS系统应力预测

Guoping Hu, Qingfeng Liu, Yu Hu, Ren-Hua Wang
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引用次数: 0

摘要

如果长时间听合成语音,人们经常会感到疲劳。这主要是因为合成语音太平淡,从不强调焦点。与传统的TTS研究方法不同,本文从听者的角度研究应力预测。首先提出了一种理想听者模型,该模型基于以下假设来预测压力分布:人们在有限的压力下说话,并将有限的压力分配给听者,以确保听者能够容易地理解说话者。然后,根据有限的研究资源,对理想听者模型进行了修正,提出了一个实用的模型。实验表明,应力预测的可接受率为87.36%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hearer model based stress prediction for Chinese TTS system
People often feel tired if they listen to synthesized speech for a long time. This is mainly because synthesized speech is too flat and never stresses the focus. Unlike traditional TTS research approaches of speaker simulation, the paper investigates stress prediction from the point of view of the hearer. An ideal hearer model is first proposed to predict the stress distribution based on the following hypothesis: people speak with limited stress effort and distribute the limited effort to ensure that the hearer can understand the speaker easily. Then, according to the limited research resource, we modify the ideal hearer model and present a practical model. Experiments show that the stress prediction achieves an acceptable rate of 87.36%.
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