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Time-frequency processing of partials for high-quality speech synthesis

机译：高质量语音合成部分的时频处理

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Based on the particularities offered by the chosen signal model, we introduce a novel approach regarding the chain of actions pursued in the analysis stage of the speech signal, which succeeds the level of partial extraction. According to the harmonic plus noise model (HNM) a number of successive estimation and synthesis operations are performed. The present paper proposes a method to enhance the harmonic parameters estimation. This new algorithm proves to have good behavior offering support in selecting an appropriate subset of partials. In addition to reducing the arithmetic complexity of the harmonic synthesis (which is known to be the most resource consuming module), this optimized selection of the partials allows us to perform a specific frequency correction, which enables the possibility of a simple and coherent future pitch manipulation. The performed experiments confirmed the expected complexity reduction. Moreover, we applied the proposed algorithm for partial selection and tracking followed by a frequency aligning of the harmonic components. The reconstructed signal compared to the original speech proved to be a perceptually indistinguishable replica.
机译：基于由所选择的信号提供模型的特殊性，我们介绍关于在语音信号中，承受局部析取的水平的分析阶段所追求操作链中的一个新的方法。根据谐波加噪声模型（HNM）多个连续的估计和合成操作的执行。本提出以增强谐波参数估计的方法。这种新的算法被证明在选择泛音适当的子集良好的行为提供支持。除了减少谐波合成的算术复杂性（这是已知的最消耗资源的模块），这优化了分音的选择使我们能够执行特定的频率校正，这使得能够简单且相干未来音调的可能性操纵。所进行的实验证实了预期的复杂度降低。此外，我们应用所提出的算法对部分选择和跟踪，随后的谐波分量的频率对准。相比于原始语音所述重构信号被证明是一个难以区分感知复制品。

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