Adaptive signal processing
Practical approaches to speech coding
Practical approaches to speech coding
Beamforming microphone arrays for speech acquisition in noisy environments
Speech Communication - Special issue on acoustic echo control and speech enhancement techniques
Multi-microphone noise reduction techniques as front-end devices for speech recognition
Speech Communication - Special issue on noise robust ASR
Discrete Time Processing of Speech Signals
Discrete Time Processing of Speech Signals
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2
Broadband Beamforming with Adaptive Postfiltering for Speech Acquisition in Noisy Environments
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
Multichannel post-filtering in nonstationary noise environments
IEEE Transactions on Signal Processing
Signal enhancement using beamforming and nonstationarity withapplications to speech
IEEE Transactions on Signal Processing
Convolutive transfer function generalized sidelobe canceler
IEEE Transactions on Audio, Speech, and Language Processing
On optimal frequency-domain multichannel linear filtering for noise reduction
IEEE Transactions on Audio, Speech, and Language Processing
Speech enhancement using Gaussian scale mixture models
IEEE Transactions on Audio, Speech, and Language Processing
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We present a novel approach for real-time multichannel speech enhancement in environments of nonstationary noise and time-varying acoustical transfer functions (ATFs). The proposed system integrates adaptive beamforming, ATF identification, soft signal detection, and multichannel postfiltering. The noise canceller branch of the beamformer and the ATF identification are adaptively updated online, based on hypothesis test results. The noise canceller is updated only during stationary noise frames, and the ATF identification is carried out only when desired source components have been detected. The hypothesis testing is based on the nonstationarity of the signals and the transient power ratio between the beamformer primary output and its reference noise signals. Following the beamforming and the hypothesis testing, estimates for the signal presence probability and for the noise power spectral density are derived. Subsequently, an optimal spectral gain function that minimizes the mean square error of the log-spectral amplitude (LSA) is applied. Experimental results demonstrate the usefulness of the proposed system in nonstationary noise environments.