Using instantaneous frequency and aperiodicity detection to estimate F0 for high-quality speech synthesis

Hideki Kawahara, Yannis Agiomyrgiannakis, H. Zen
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引用次数: 29

Abstract

This paper introduces a general and flexible framework for F0 and aperiodicity (additive non periodic component) analysis, specifically intended for high-quality speech synthesis and modification applications. The proposed framework consists of three subsystems: instantaneous frequency estimator and initial aperiodicity detector, F0 trajectory tracker, and F0 refinement and aperiodicity extractor. A preliminary implementation of the proposed framework substantially outperformed (by a factor of 10 in terms of RMS F0 estimation error) existing F0 extractors in tracking ability of temporally varying F0 trajectories. The front end aperiodicity detector consists of a complex-valued wavelet analysis filter with a highly selective temporal and spectral envelope. This front end aperiodicity detector uses a new measure that quantifies the deviation from periodicity. The measure is less sensitive to slow FM and AM and closely correlates with the signal to noise ratio.
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使用瞬时频率和非周期检测来估计高质量语音合成的F0
本文介绍了F0和非周期(加性非周期分量)分析的通用和灵活的框架,专门用于高质量的语音合成和修改应用。该框架由瞬时频率估计和初始非周期检测器、F0轨迹跟踪器、F0细化和非周期提取器三个子系统组成。提出的框架的初步实现在跟踪时间变化的F0轨迹的能力方面大大优于现有的F0提取器(在RMS F0估计误差方面是10倍)。前端非周期检测器由具有高选择性时域和频谱包络的复值小波分析滤波器组成。这种前端非周期检测器采用了一种量化周期性偏差的新方法。该测量对慢速调频和调幅不太敏感,且与信噪比密切相关。
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