Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Multichannel Direction-Independent Speech Enhancement Using Spectral Amplitude Estimation Thomas Lotter | EURASIP Journal on Applied Signal Processing 2003 11 1147-1156 2003 Hindawi Publishing Corporation Multichannel Direction-Independent Speech Enhancement Using Spectral Amplitude Estimation Thomas Lotter Institute of Communication Systems and Data Processing Aachen University RWTH Templergraben 55 D-52056 Aachen Germany Email lotter@ Christian Benien Philips Research Center Aachen Weifihausstrafie 2 D-52066 Aachen Germany Email Peter Vary Institute of Communication Systems and Data Processing Aachen University RWTH Templergraben 55 D-52056 Aachen Germany Email vary@ Received 25 November 2002 and in revised form 12 March 2003 This paper introduces two short-time spectral amplitude estimators for speech enhancement with multiple microphones. Based on joint Gaussian models of speech and noise Fourier coefficients the clean speech amplitudes are estimated with respect to the MMSE or the MAP criterion. The estimators outperform single microphone minimum mean square amplitude estimators when the speech components are highly correlated and the noise components are sufficiently uncorrelated. Whereas the first MMSE estimator also requires knowledge of the direction of arrival the second MAP estimator performs a direction-independent noise reduction. The estimators are generalizations of the well-known single channel MMSE estimator derived by Ephraim and Malah 1984 and the MAP estimator derived by Wolfe and Godsill 2001 respectively. Keywords and phrases speech enhancement microphone arrays spectral amplitude estimation. 1. INTRODUCTION Speech communication appliances such as voice-controlled devices hearing aids and hands-free telephones often suffer from poor speech quality due to background noise and room reverberation. Multiple microphone techniques such as beamformers can improve the speech quality and intelligibility by exploiting the spatial diversity of speech and noise sources. Upon these techniques one
