| Paper: | SP-P10.2 | ||
| Session: | Topics in Speech Enhancement | ||
| Time: | Wednesday, May 19, 15:30 - 17:30 | ||
| Presentation: | Poster | ||
| Topic: | Speech Processing: Speech Enhancement | ||
| Title: | SPEECH ENHANCEMENT BY PERCEPTUAL FILTER WITH SEQUENTIAL NOISE PARAMETER ESTIMATION | ||
| Authors: | Te-Won Lee; University of California, San Diego | ||
| Kaisheng Yao; University of California, San Diego | |||
| Abstract: | We report a work on speech enhancement that combines sequential noise estimation and perceptual filtering. The sequential estimation employs an extension of the sequential EM-type algorithm. In this algorithm, statistics of clean speech are modeled by hidden Markov models (HMM) and noise is assumed to be Gaussian distributed with a time-varying mean vector (the noise parameter) to be estimated. The estimation process uses a non-linear function that relates speech statistics, noise, and noisy observation. With the estimated noise parameter, subtraction-type algorithm for speech enhancement may be extended to non-stationary environments. In particular, a perceptual filter with frequency masking is constructed with a tradeoff between noise reduction and speech distortion considering the sensitivity of speech recognition systems to speech distortion. Our experiments in speech enhancement and speech recognition in non-stationary noise confirmed that this approach seems promising in improving performances compared to alternative speech enhancement algorithms. | ||
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