Effective jointly pdf-based voice activity detector for real-time applications

被引：2

作者：

Gorriz, J. M. ^{[1
]}

Ramirez, J.

Puntonet, C. G.

机构：

[1] C Periodista Daniel Saucedo Arnada, Dept Signal Theory Networking & Commun, Granada 18071, Spain

[2] C Periodista Daniel Saucedo Arnada, Dept Architecture & Comp Technol, Granada 18071, Spain

来源：

ELECTRONICS LETTERS | 2007年 / 43卷 / 04期

关键词：

D O I：

10.1049/el:20073742

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Presented is an accurate speech detection algorithm based on a jointly Gaussian probability distribution function (JGpdf) and a likelihood ratio test evaluated on a new observation model for the input speech. A more realistic description of the dependence between observations in a classical statistical binary framework (H0&H1) provides higher discrimination in speech endpoint detection and reports benefits over a number of recently published methods.

引用

页码：251 / 253

页数：3

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