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Towards Hierarchical Prosodic Prominence Generation in TTS Synthesis

机译:走向TTS合成中的分层韵律突出

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We address the problem of identification (from text) and generation of pitch accents in HMM-based English TTS synthesis. We show, through a large scale perceptual test, that a large improvement of the binary discrimination between pitch accented and non-accented words has no effect on the quality of the speech generated by the system. On the other side adding a third accent type that emphatically marks words that convey "contrastive" focus (automatically identified from text) produces beneficial effects on the synthesized speech. These results support the accounts on prosodic prominence that consider the prosodic patterns of utterances as hierarchical structured and point out the limits of a flattening of such structure resulting from a simple accenton-accent distinction.
机译:我们解决了基于HMM的英语TTS合成中的识别(从文本)和音高重音生成的问题。我们通过大规模的感知测试表明,音高重音词和非重音词之间的二进制区别的大幅度改善对系统生成的语音质量没有影响。另一方面,添加了第三种重音类型,该重音类型突出标记了传达“对比”焦点的单词(自动从文本中识别),从而对合成语音产生了有益的影响。这些结果支持关于韵律突出的说明,这些说明将语音的韵律模式视为层次结构,并指出了由于简单的重音/非重音区别而导致这种结构变平的局限性。

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