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Estimation of Pitch Targets from Speech Signals by Joint Regularized Optimization

机译:基于联合正则优化的语音信号音高目标估计

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This paper presents a novel method to estimate the pitch target parameters of the target approximation model (TAM). The TAM allows the compact representation of natural pitch contours on a solid theoretical basis and can be used as an intonation model for text-to-speech synthesis. In contrast to previous approaches, the method proposed here estimates the parameters of all targets jointly, uses 5th-order (instead of 3rd-order) linear systems to model the target approximation process, and uses regularization to avoid unnatural pitch targets. The effect of these features on the modeling error and the target parameter distributions are shown. The proposed method has been made available as the open-source software tool TargetOptimizer.
机译:本文提出了一种新的方法来估计目标近似模型(TAM)的俯仰目标参数。 TAM可以在坚实的理论基础上紧凑地表示自然的音高轮廓,并且可以用作文本到语音合成的语调模型。与以前的方法相比,这里提出的方法联合估计所有目标的参数,使用5阶(而不是3阶)线性系统对目标逼近过程进行建模,并使用正则化来避免不自然的音调目标。显示了这些特征对建模误差和目标参数分布的影响。所提出的方法已作为开源软件工具TargetOptimizer提供。

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