Signal Processing
Subjective comparison and evaluation of speech enhancement algorithms
Speech Communication
Speech enhancement by map spectral amplitude estimation using a super-Gaussian speech model
EURASIP Journal on Applied Signal Processing
A noise reduction preprocessor for mobile voice communication
EURASIP Journal on Applied Signal Processing
Denoising in the domain of spectrotemporal modulations
EURASIP Journal on Audio, Speech, and Music Processing
A time--frequency approach for noise reduction
Digital Signal Processing
On the use of Kalman filter for enhancing speech corrupted by colored noise
WSEAS Transactions on Signal Processing
An energy-efficient target tracking framework in wireless sensor networks
EURASIP Journal on Advances in Signal Processing
On the improvement of singing voice separation for monaural recordings using the MIR-1K dataset
IEEE Transactions on Audio, Speech, and Language Processing
Conventional beamformer using post-filter for speech enhancement
ICHIT'06 Proceedings of the 1st international conference on Advances in hybrid information technology
Bayesian marginal statistics for speech enhancement using log Gabor wavelet
International Journal of Speech Technology
Impact of SNR and gain-function over- and under-estimation on speech intelligibility
Speech Communication
MCRA noise estimation for KLT-VRE-based speech enhancement
International Journal of Speech Technology
Perceptual subspace speech enhancement using variance of the reconstruction error
Digital Signal Processing
Computers and Electrical Engineering
International Journal of Speech Technology
International Journal of Speech Technology
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This paper addresses the problem of single microphone frequency domain speech enhancement in noisy environments. The main characteristics of available frequency domain noise reduction algorithms are presented. We have confirmed that the a priori SNR estimation leads to the best subjective results. According to these conclusions, a new approach is then developed which achieves a trade-off between effective noise reduction and low computational load for real-time operations. The obtained solutions demonstrate that the subjective and objective results are much better than existing methods.