DocumentCode :
431851
Title :
Multi-channel speech dereverberation based on a statistical model of late reverberation
Author :
Habets, E. A P
Author_Institution :
Dept. of Electr. Eng., Technische Universiteit Eindhoven, Netherlands
Volume :
4
fYear :
2005
fDate :
18-23 March 2005
Abstract :
Speech signals recorded with a distant microphone usually contain reverberation, which degrades the fidelity and intelligibility of speech, and the recognition performance of automatic speech recognition systems. A multi-channel speech dereverberation algorithm is presented which reduces spectral coloration and late reverberation. A spatially averaged amplitude spectrum is used to estimate the instantaneous amplitude spectrum of the clean speech signal, which is then further enhanced using an estimate of the power spectrum of the late reverberant signal. The power spectrum of the late reverberant signal is constructed from multiple microphone signals and a statistical model of late reverberation. The algorithm is tested using synthetic reverberated signals. The performances for different room impulse responses with reverberation times ranging from approximately 150 ms to 350 ms show significant reverberation reduction with little signal distortion.
Keywords :
acoustic distortion; acoustic signal processing; parameter estimation; reverberation; spectral analysis; speech enhancement; speech intelligibility; statistical analysis; transient response; automatic speech recognition systems; clean speech signal; instantaneous amplitude spectrum estimation; late reverberation; multichannel speech dereverberation; multiple microphone signals; reverberation times; room impulse response; signal distortion; signal power spectrum estimation; spatially averaged amplitude spectrum; spectral coloration; speech enhancement; speech fidelity; speech intelligibility; statistical model; synthetic reverberated signals; Acoustic distortion; Acoustic noise; Amplitude estimation; Automatic speech recognition; Degradation; Microphones; Reverberation; Signal processing algorithms; Stochastic processes; Tail;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
ISSN :
1520-6149
Print_ISBN :
0-7803-8874-7
Type :
conf
DOI :
10.1109/ICASSP.2005.1415973
Filename :
1415973
Link To Document :
بازگشت