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Speech Endpoint Detection in Noisy Environments Using EMD and Teager Energy Operator 被引量:4
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作者 de-xiang zhang xiao-pei wu zhao lv 《Journal of Electronic Science and Technology》 CAS 2010年第2期183-186,共4页
Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition (EMD) algorithm and Teager energy operator (TEO) is proposed to l... Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition (EMD) algorithm and Teager energy operator (TEO) is proposed to locate endpoint intervals of a speech signal embedded in noise. With the EMD, the noise signals can be decomposed into different numbers of sub-signals called intrinsic mode functions (IMFs), which is a zero-mean AM-FM component. Then TEO can be used to extract the desired feature of the modulation energy for IMF components. In order to show the effectiveness of the proposed method, examples are presented to show that the new measure is more effective than traditional measures. The present experimental results show that the measure can be used to improve the performance of endpoint detection algorithms and the accuracy of this algorithm is quite satisfactory and acceptable. 展开更多
关键词 Index Terms----Empirical mode decomposition endpoint detection noisy speech Teager energy operator.
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