基于幅度压缩滤波的清浊音分类及基音估计

doi:10.11999/JEIT150778

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Abstract

A method of voiced/unvoiced classification and pitch estimation based on Pitch Estimation Filter with Amplitude Compression (PEFAC) is proposed in this paper. The method first attenuates strong noise components at the?low frequencies based on PEFAC and extracts pitch harmonic from noisy speech in the log-frequency domain. Then, the harmonic number associated with the pitch harmonic is determined by Symmetric average magnitude sum function weighted Impulse-train Matching (SIM) scheme in time domain. A pitch tracking scheme using dynamic programming is applied to select the pitch candidates and a voiced speech probability is computed from the likelihood ratio of Gaussian Mixture Models (GMMs) classifiers based on 3-element feature vector. The simulated results show that the proposed method efficiently reduces voiced/unvoiced and pitch estimation error, and it is superior to some of the state-of-the–art method in the real environment.

Key words： Speech signal processing Pitch Pitch Estimation Filter with Amplitude Compression (PEFAC) Symmetric average magnitude sum function Gaussian Mixture Model (GMM) Noise speech

Received: 29 June 2015 Published: 03 February 2016

PACS:

TN912.3

Fund:

The National Natural Science Foundation of China (61271248), The Natural Science Foundation of Huzhou City (2015YZ04)

Corresponding Authors: ZHAO Xiaoqun E-mail: zhao_xiaoqun@tongji.edu.cn

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	XU Jingyun
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	WANG Qiao
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Cite this article:

XU Jingyun,ZHAO Xiaoqun,WANG Qiao等. Voiced/Unvoiced Classification and Pitch Estimation Based on Amplitude Compression Filter[J]. JEIT, 2016, 38(3): 586-593.

URL:

http://jeit.ie.ac.cn/EN/10.11999/JEIT150778 OR http://jeit.ie.ac.cn/EN/Y2016/V38/I3/586

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