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Optimal weight tuning method for unit selection cost functions in syllable based text-to-speech synthesis

机译:基于音节的语音合成中单位选择成本函数的最优权重调整方法

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This paper proposes a method for tuning the weights of unit selection cost functions in syllable based text-to-speech (TTS) synthesis system. In this work, unit selection cost functions, namely target cost and concatenation cost, are designed appropriate to syllables. The method tunes the weights in such a way that perceptual preference patterns are appropriately considered while selecting the units. The method uses genetic algorithm to derive the optimal weights. Fitness function is designed to map perceptual preference patterns into weights of unit selection cost functions. The effectiveness of proposed method is evaluated by both subjective and objective measures. From the results, it is observed that the derived optimal weights can synthesize good quality speech compared to manually tuned weights.
机译:本文提出了一种基于音节的语音合成系统,用于调整单位选择成本函数权重的方法。在这项工作中,单元选择成本函数即目标成本和串联成本被设计为适合音节。该方法以这样的方式调整权重,使得在选择单位时适当考虑感知偏好模式。该方法使用遗传算法来得出最佳权重。适应度函数旨在将感知偏好模式映射到单位选择成本函数的权重。所提出方法的有效性通过主观和客观措施进行评估。从结果可以看出,与手动调整的权重相比,导出的最佳权重可以合成高质量的语音。

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