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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Roman, N. DeLiang Wang |
| Copyright Year | 2004 |
| Description | Author affiliation: Dept. of Comput. & Inf. Sci., Ohio State Univ., Columbus, OH, USA (Roman, N.; DeLiang Wang) |
| Abstract | We present a novel method for binaural sound segregation from acoustic mixtures contaminated by both multiple interference and reverberation. We employ the notion of an ideal time-frequency binary mask, which selects the target if it is stronger than the interference in a local time-frequency (T-F) unit. As opposed to classical adaptive filtering, which focuses on the suppression of noise, our model employs an adaptive filter that performs target cancellation. T-F units dominated by a target are largely suppressed at the output of the cancellation unit when compared to units dominated by noise. Consequently, the actual input-to-output attenuation level in each T-F unit is used to estimate an ideal binary mask. A systematic evaluation in terms of automatic speech recognition performance shows that the resulting system produces masks close to ideal binary ones. |
| File Size | 554920 |
| File Format | |
| ISBN | 0780384849 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2004.1326272 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-05-17 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Reverberation Interference Adaptive filters Acoustic noise Time frequency analysis Noise cancellation Attenuation Degradation Automatic speech recognition Delay effects |
| Content Type | Text |
| Resource Type | Article |
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