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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Nemala, S.K. Elhilali, M. |
| Copyright Year | 2012 |
| Description | Author affiliation: Department of Electrical and Computer Engineering, Center for Speech and Language Processing, The Johns Hopkins University, Baltimore, MD 21218, USA (Nemala, S.K.; Elhilali, M.) |
| Abstract | In the real world, natural conversational speech is an amalgam of speech segments, silences and environmental/ background and channel effects. Labeling the different regions of an acoustic signal according to their information levels would greatly benefit all automatic speech processing tasks. In the current work, we propose a novel segmentation approach based on a perception-based measure of speech intelligibility. Unlike segmentation approaches based on various forms of voice-activity detection (VAD), the proposed parsing approach exploits higher-level perceptual information about signal intelligibility levels. This labeling information is integrated into a novel multilevel framework for automatic speaker recognition task. The system processes the input acoustic signal along independent streams reflecting various levels of intelligibility and then fusing the decision scores from the multiple steams according to their intelligibility contribution. Our results show that the proposed system achieves significant improvements over standard baseline and VAD-based approaches, and attains a performance similar to the one obtained with oracle speech segmentation information. |
| Starting Page | 4393 |
| Ending Page | 4396 |
| File Size | 107966 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467300452 |
| ISSN | 15206149 |
| e-ISBN | 9781467300469 |
| e-ISBN | 9781467300445 |
| DOI | 10.1109/ICASSP.2012.6288893 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-03-25 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Speech Multilevel systems Speech recognition Acoustics Speaker recognition Speech processing NIST Noise robustness Speech intelligibility Voice-activity detection |
| Content Type | Text |
| Resource Type | Article |
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