We propose a new algorithm to suppress both stationary background noise and nonstationary directional interference noise in a speech enhancement system that employs the generalized sidelobe canceller. Our approach builds on advances in generalized sidelobe canceller design involving the transfer function ratio. Our system is composed of three stages. The first stage estimates the transfer function ratio on the acoustic path, from the nonstationary directional interference noise source to the microphones, and the powers of the stationary background noise components. Secondly, the estimated powers of the stationary background noise components are used to execute spectral subtraction with respect to input signals. Finally, the estimated transfer function ratio is used for speech enhancement on the primary channel, and an adaptive filter reduces the residual correlated noise components of the signal. These algorithmic improvements give consistently better performance than the transfer function generalized sidelobe canceller when input signal-to-noise ratio is 10 dB or lower.
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Artificial Intelligence
- Hardware and Architecture
- Computer Vision and Pattern Recognition