An integrated real-time beamforming and postfiltering system for nonstationary noise environments
EURASIP Journal on Applied Signal Processing
Postfiltering using multichannel spectral estimation in multispeaker environments
EURASIP Journal on Advances in Signal Processing
Adaptive β-order generalized spectral subtraction for speech enhancement
Signal Processing
A Two-Microphone Noise Reduction Method in Highly Non-stationary Multiple-Noise-Source Environments
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Multi-channel noise reduction in noisy environments
ISCSLP'06 Proceedings of the 5th international conference on Chinese Spoken Language Processing
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In this paper, we present a multichannel post-filtering approach for minimizing the log-spectral amplitude distortion in nonstationary noise environments. The beamformer is realistically assumed to have a steering error, a blocking matrix that is unable to block all of the desired signal components, and a noise canceller that is adapted to the pseudo-stationary noise but not modified during transient interferences. A mild assumption is made that a desired signal component is stronger at the beamformer output than at any reference noise signal, and a noise component is strongest at one of the reference signals. The ratio between the transient power at the beamformer output and the transient power at the reference noise signals is used to indicate whether such a transient is desired or interfering. Based on a Gaussian statistical model and combined with an appropriate spectral enhancement technique, we derive estimators for the signal presence probability, the noise power spectral density, and the clean signal. The proposed method is tested in various nonstationary noise environments. Compared with single-channel post-filtering, a significantly reduced level of nonstationary noise is achieved without further distorting the desired signal components.