首页> 外文会议>Speech Technology and Human-Computer Dialogue, 2009. SpeD '09 >Time-frequency processing of partials for high-quality speech synthesis
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Time-frequency processing of partials for high-quality speech synthesis

机译:用于高质量语音合成的部分的时频处理

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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:基于所选信号模型提供的特殊性,我们介绍了一种有关语音信号分析阶段所追求的动作链的新颖方法,该方法成功了部分提取的水平。根据谐波加噪声模型(HNM),执行了许多连续的估计和合成操作。本文提出了一种增强谐波参数估计的方法。事实证明,此新算法具有良好的行为,可为选择适当的部分子集提供支持。除了降低谐波合成的算法复杂度(众所周知,它是最消耗资源的模块)之外,这种优化的分音选择还使我们能够执行特定的频率校正,从而有可能实现简单而连贯的未来音高操纵。进行的实验证实了预期的复杂性降低。此外,我们将提出的算法用于部分选择和跟踪,然后对谐波分量进行频率对准。与原始语音相比,重建后的信号被证明是在感知上无法区分的副本。

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