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Pitch-Asynchronous Overlap-Add Waveform-Concatenation Speech Synthesis by Using a Phase-Optimizing Neural Network

机译:通过使用相位优化神经网络,俯仰异步重叠 - 添加波形串联语音合成

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The pitch-synchronous overlap-add (PSOLA) speech synthesis method has been conventionally used for a high-quality waveform-concatenation. The basis lies in the periodic structure of voiced speech, i.e., the pitchmark. Though the PSOLA-synthesized sound has a high quality so far as the pitchmark detection is successful, it is sometimes degraded to a great extent when it fails to detect the pitchmark or, more fundamentally, when the sound is unvoiced consonant. In this paper, we propose a pitch-asynchronous waveform-concatenation speech synthesis method. It is based on an adaptive phase optimization by using a complex-valued neural processing to maintain a desirable degree of pulse sharpness. Experimental results demonstrate a successful generation of high-quality sound.
机译:距离同步重叠 - 添加(PSOLA)语音合成方法通常用于高质量的波形级联。基础位于浊音语音的周期性结构中,即,凝聚氧化织片。虽然PSOLA合成的声音具有高质量的凝聚标记检测成功,但在很大程度上在很大程度上降低了当声音是无声辅音时,它有时会在很大程度上降级。在本文中,我们提出了一种俯仰异步波形 - 倾斜语音合成方法。它通过使用复值的神经处理来基于自适应相位优化,以保持所需的脉冲清晰度。实验结果表明了成功的高质量声音。

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