| Paper: | SAM-P7.6 | ||
| Session: | Applications of Multichannel Signal Processing | ||
| Time: | Thursday, May 20, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Sensor Array and Multichannel Signal Processing: Source localization, separation, classification, and tracking | ||
| Title: | BINAURAL SOUND SEGREGATION FOR MULTISOURCE REVERBERANT ENVIRONMENTS | ||
| Authors: | Nicoleta Roman; Ohio State University | ||
| DeLiang Wang; Ohio State University | |||
| Abstract: | We present a novel method for binaural sound segregation from acoustic mixtures contaminated by both multiple interferences 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 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. | ||
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