The Voice Segment Type Determination using the Autocorrelation Compared to Cepstral Method

OLDRICH HORAK

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The Voice Segment Type Determination using the Autocorrelation Compared to Cepstral Method

机译：使用自相关与倒谱方法进行语音段类型确定

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The extraction of the characteristic features of the speech is the important task in the speaker recognition process. One of the basic features is fundamental frequency of speaker's voice, which can be extracted from the voiced segment of the speech signal. This document describes one of the methods providing possibility to distinguish the voiced and surd segments of the voice signal using the autocorrelation, and compare the results to cepstral method.

机译：语音特征的提取是说话人识别过程中的重要任务。基本特征之一是扬声器语音的基频，该基频可以从语音信号的有声段中提取。该文件描述了一种方法，该方法提供了使用自相关来区分语音信号的浊音段和突波段并将结果与倒谱方法进行比较的可能性。

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《WSEAS Transactions on Signal Processing》 |2012年第4期|共10页
作者
OLDRICH HORAK;
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原文格式 PDF
正文语种 eng
中图分类声学;
关键词
Autocorrelation; Cepstrum; Features extraction; Fundamental frequency; Signal processing; Speaker recognition; Voice signal;

机译：自相关;倒谱;特征提取;基本频率;信号处理;说话人识别;语音信号;

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1. The Voice Segment Type Determination using the Autocorrelation Compared to Cepstral Method [J] . OLDRICH HORAK WSEAS Transactions on Signal Processing . 2012,第1a4期

机译：使用自相关与倒谱方法进行语音段类型确定
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7. Autocorrelation-based noise subtraction method with smoothing, overestimation, energy, and cepstral mean and variance normalization for noisy speech recognition [O] . Gholamreza Farahani 2017

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The Voice Segment Type Determination using the Autocorrelation Compared to Cepstral Method

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