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ENDPOINT DETECTOR OF NOISY SPEECH SIGNAL USING A RECURRENT NEURAL NETWORK

ENDPOINT DETECTOR OF NOISY SPEECH SIGNAL USING A RECURRENT NEURAL NETWORK
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摘要 IntroductionEndpointdetectionofspeechsignalisimportantinmanyareasofspeechprocessingtechnology,suchasspeechenhancement,speechr... In real applications, speech signal is usually corrupted by background noise, which greatly affects the performance of speech processing systems. This paper addressed the important problem of noisy speech endpoint detection in robust speech recognition or other speech processing areas. As the traditional energy based method for speech endpoint detection had poor poerformance in low signal to noise ratio, a novel speech endpoint detector was proposed. This approach takes advantages of a Recurrent Neural Network (RNN) to determine speech activity. The RNN, which is trained to be insensitive to noise variation, shows good behavior in the test experiments.
出处 《Journal of Shanghai Jiaotong university(Science)》 EI 1999年第1期60-63,共4页 上海交通大学学报(英文版)
关键词 SPEECH ENDPOINT detection RECURRENT NEURAL network(RNN) immunity learning speech endpoint detection recurrent neural network(RNN) immunity learning
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