| Paper: | SP-P8.2 | ||
| Session: | Voice Activity Detection and Speech Segmentation | ||
| Time: | Wednesday, May 19, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Speech Processing: Feature Extraction | ||
| Title: | SPEECH DISCRIMINATION BASED ON MULTISCALE SPECTRO-TEMPORAL MODULATIONS | ||
| Authors: | Nima Mesgarani; University of Maryland, College Park | ||
| Shihab Shamma; University of Maryland, College Park | |||
| Malcolm Slaney; IBM Almaden Research Center | |||
| Abstract: | A novel approach for content-based audio classification is presented based on multiscale spectro-temporal modulation features extracted using a model of auditory cortex. The task is to discriminate speech from non-speech which consists of animal vocalizations, music and environmental sounds. Generalization of the system to signals in high level of additive noise andreverberation is evaluated and compared to two existing approaches. The results demonstrate the advantages of the auditory model over the other two systems, especially at low SNRs and high reverberation. | ||
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