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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Nathwani, K. Padaki, H. Hegde, R.M. |
| Copyright Year | 2013 |
| Description | Author affiliation: Dept. of Electr. Eng., Indian Inst. of Technol. Kanpur, Kanpur, India (Nathwani, K.; Padaki, H.; Hegde, R.M.) |
| Abstract | In this work, a method for multi channel speech enhancement using linear prediction (LP) residual cepstrum is proposed. The method performs deconvolution at each microphone output using cepstral domain. The deconvolution of acoustic impulse response from reverberated signal in each individual channel removes early reverberation. This dereverberated output from each channel is then spatially filtered using delay and sum beamformer (DSB). The late reverberation components are then removed by temporal averaging of the glottal closure instants (GCI) computed using the dynamic programming projected phase-slope algorithm (DYPSA). The GCI obtained herein correspond to the LP residual peaks. These residual peaks are excluded from the averaging process, since they have significant impact on speech quality and should remain unmodified. The experiments on subjective and objective evaluation are conducted on TIMIT and MONC databases for proposed method and compared with other methods. The experimental results of proposed method on speech dereverberation and distant speech recognition indicate reasonable improvement over conventional methods. |
| Sponsorship | IEEE Signal Process. Soc. |
| Starting Page | 555 |
| Ending Page | 559 |
| File Size | 627880 |
| Page Count | 5 |
| File Format | |
| e-ISBN | 9781479923908 |
| DOI | 10.1109/ACSSC.2013.6810340 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-11-03 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Speech Speech enhancement Reverberation Cepstrum Microphones Databases |
| Content Type | Text |
| Resource Type | Article |
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