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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Cao Yali La Dongsheng Jia Shuo Niu Xuefen |
| Copyright Year | 2014 |
| Description | Author affiliation: Northeastern Univ. at Qinhuangdao, Qinhuangdao, China (Cao Yali; La Dongsheng; Jia Shuo; Niu Xuefen) |
| Abstract | This paper highlights the sub-band average energy variance (SBAEV) approach to perform the endpoint detection process, which involves the segmentation of speech signals from non-speech signals. The SBAEV models have been proposed to perform endpoint detections of isolated digit utterances spoken in the Language. Experiment results obtained from this method are acoustically verified, visually checked and compared to the conventional method of endpoint detection. It was found that the endpoint detection accuracy using the SBAEV approach is very high and encouraging.. |
| Starting Page | 3010 |
| Ending Page | 3012 |
| File Size | 134004 |
| Page Count | 3 |
| File Format | |
| ISBN | 9781479937073 |
| e-ISBN | 9781479937080 |
| DOI | 10.1109/CCDC.2014.6852690 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-05-31 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wavelet transforms Wavelet domain endpoint detection wavelet transforms Noise Speech Wavelet analysis Speech processing sub-band average energy variance |
| Content Type | Text |
| Resource Type | Article |
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