Endpoint detection of speech signal using neural network

被引：0

作者：

Hussain, A ^{[1
]}

Samad, SA ^{[1
]}

Fah, LB ^{[1
]}

机构：

[1] Univ Kebangsaan Malaysia, Fac Engn, Dept Elect Elect & Syst Engn, Multimedia Signal Proc Res Grp, Bangi 43600, Malaysia

来源：

IEEE 2000 TENCON PROCEEDINGS, VOLS I-III: INTELLIGENT SYSTEMS AND TECHNOLOGIES FOR THE NEW MILLENNIUM | 2000年

关键词：

speech segmentation; speech recognition;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper highlights the artificial neural network (ANN) approach to perform the endpoint detection process, which involves the segmentation of speech signals from non-speech signals. Two ANN models have been proposed to perform endpoint detections of isolated digit utterances spoken in the Malay Language: Multilayer Perceptron (MLP) and Adaptive Linear Network (ADALINE). Results obtained from the ANN models are acoustically verified, visually checked and compared to the conventional method of endpoint detection. It was found that the endpoint detection accuracy using the MLP approach is very high and encouraging.

引用

页码：271 / 274

页数：4

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