小波包倒谱分析在说话人识别中的应用

Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002. Pub Date : 2002-11-03 DOI:10.1109/ACSSC.2002.1197177

A. Kinney, J. Stevens

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引用次数: 8

摘要

介绍了一种新的说话人识别处理技术。结果表明，基于小波包分解的倒谱分析的特征提取可以有效地分离说话人之间的语音。这个想法是基于声道和激励源成分的反卷积，通过信号的多分辨率小波的同态分解。采用简单的神经网络技术对小波包倒谱分析得到的特征向量进行分类。

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Wavelet packet cepstral analysis for speaker recognition

A novel processing technique for speaker recognition applications is introduced. It was shown that feature extraction based on cepstral analysis of the wavelet packet decomposition can provide significant inter-speaker separation. This idea is based on deconvolution of the vocal tract and excitation source components through homomorphic decomposition of a signal's multiresolution wavelets. A simple neural network technique is employed to classify the feature vector obtained through wavelet packet cepstral analysis.

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Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002.

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