Speech Discrimination Based on Multiscale Spectro-Temporal Modulations (ISR IP)
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Nima Mesgarani, Shihab Shamma
U.S. Patent: 7,505,902
Researchers at the University of Maryland have developed a content-based audio classification algorithm based on novel multiscale spectro-temporal modulation features inspired by cortical processing.
A potential use for the classification system is to discriminate speech from non-speech. Non-speech, for example, could consist of animal vocalizations, music, or environmental sounds. In head-to-head comparisons with two other state-of the-art approaches to discriminating between speech and non-speech, the multiscale spectro-temporal system performed significantly better.
These algorithms also have applications in audio and data retrieval, archival management, modern human-computer interfaces, and in the entertainment and security industries. The researchers are also working on developing algorithms to enhance speech in noisy environments using an auditory model.
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Published June 21, 2007