Statistical Array Geometries for Real-Time Covert Surveillance with Parallel Computer Implementations

Grants and Contracts Details

Description

The proposed work focuses on developing masking algorithms to extract weak voices in cocktail party environments using distributed microphones. This builds on previous work where it was demonstrated that signals from distributed microphones can be used to create time-frequency masking patterns that suppress interfering voices and significantly increase intelligibility over beamforming alone. The student funded by this proposal will develop algorithms to reduce the need for knowing precise microphone locations through auto-tuning the steering vectors, and will explore other time-frequency decomposition methods with the potential to reduce distortion from the masking operations. While previous/current work has considered auto-tuning, more refinement in the optimization processes is required to find the weak local minima in the steeredresponse power of the distributed microphone beamformer, which represents the weaker targets. In addition, current time-frequency masking uses regular time-frequency intervals based on an short-time FFT decomposition. Wavelet packets have the potential window the time-frequency space in a way more compatible with speech signals and human auditory processing. The use of wavelet packet will be explored to determine best basis patterns for improving intelligibility and reducing distortion. Experiments based on real recordings and simulations will be performed for developing and testing performance. Best performing algorithms will be packaged in graphical user interfaces for use by the sponsor.
StatusFinished
Effective start/end date6/4/127/3/13

Funding

  • Federal Bureau of Investigation: $24,594.00

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