A Directionally Tunable but Frequency-Invariant Beamformer for an “Acoustic Velocity-Sensor Triad” to Enhance Speech Perception

Herein presented is a simple microphone-array beamformer that is independent of the frequency-spectra of all signals, all interference, and all noises. This beamformer allows/requires the listener to tune the desired azimuth-elevation “look direction.” No prior information is needed of the interference. The beamformer deploys a physically compact triad of three collocated but orthogonally oriented velocity sensors. These proposed schemes’ efficacy is verified by a jury test, using simulated data constructed with speech samples. For example, a desired speech signal, originally at a very adverse signal-to-interference-and-noise power ratio (SINR) of -30 dB, may be processed to become fully intelligible to the jury.

Speaker Details

Professor Wong received a B.S.E. degree in chemical engineering from UCLA and a Ph.D. in E.C.E. from Purdue University (West Lafayette, Indiana). He was on the senior professional staff in the Johns Hopkins University Applied Physics Laboratory (Laurel, Maryland). Later in 1998 to 2006, he was an assistant professor in Singapore, Hong Kong, and Canada. Since 2006, he has been an associate professor in the Hong Kong Polytechnic University. Thomas is currently an associate editor for the IEEE Trans. on Signal Processing, the IEEE Trans. on Aerospace & Electronic Systems, and the IEEE Trans. on Vehicular Technology. His current research interests include microphone array signal processing, source localization algorithms, and soundscape signal separation.

Series:
Microsoft Research Talks
Date:
Speakers:
Kainam Thomas Wong
Affiliation:
Hong Kong Polytechnic University

Series: Microsoft Research Talks