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引用次数: 16

摘要

串联合成可以产生高质量的语音,但受限于数据库中捕获的语音变体和语音类型。需要修改语音单元以消除共振不连续,并创建新的说话风格,例如低或高发音。不幸的是,操纵频谱结构往往会导致语音质量下降。研究了基于反滤波和正弦建模的两种语音修饰策略,并分析了它们在改变语音频谱包络方面的优缺点。然后,我们提出了一种使用正弦建模的方法,并用全极模型表示复正弦振幅。全极模型在振幅域和相位域都能很好地逼近正弦频谱。我们使用正弦波+全极模型来控制录制语音的频谱包络。利用正弦合成从模型中生成高质量的修改语音。实验结果表明,该模型能够有效地改变元音身份,优于残差LPC。
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Spectral modification for concatenative speech synthesis
Concatenative synthesis can produce high-quality speech but is limited to the allophonic variations and voice types that were captured in the database. It would be desirable to modify speech units to remove formant discontinuities and to create new speaking styles, such as hypo- or hyper-articulated speech. Unfortunately, manipulating the spectral structure often leads to degraded speech quality. We investigate two speech modification strategies, one based on inverse filtering and the other on sinusoidal modeling, and we explain their merits and shortcomings for changing the spectral envelope in speech. We then propose a method which uses sinusoidal modeling and represents the complex sinusoidal amplitudes by an all-pole model. The all-pole model approximates the sinusoidal spectrum well, both in the amplitude and in the phase domain. We use the sinusoidal+all-pole model to control the spectral envelope in recorded speech. High-quality modified speech is generated from the model using sinusoidal synthesis. A perceptual test was conducted, which shows that the model was effective at changing vowel identities and was preferable over residual excited LPC.
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