A Noise Reduction Preprocessor for Mobile Voice Communication
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A Noise Reduction Preprocessor for Mobile Voice Communication Rainer Martin Institute of Communication Acoustics, Ruhr-University Bochum, 44780 Bochum, Germany Email: [email protected]
David Malah Department of Electrical Engineering, Technion – Israel Institute of Technology, Haifa 32000, Israel Email: [email protected]
Richard V. Cox AT&T Labs-Research, 180 Park Avenue, Florham Park, NJ 07932, USA Email: [email protected]
Anthony J. Accardi Tellme Networks, 1310 Villa Avenue, Mountain View, CA 94041, USA Email: [email protected] Received 15 September 2003; Revised 20 November 2003; Recommended for Publication by Piet Sommen We describe a speech enhancement algorithm which leads to significant quality and intelligibility improvements when used as a preprocessor to a low bit rate speech coder. This algorithm was developed in conjunction with the mixed excitation linear prediction (MELP) coder which, by itself, is highly susceptible to environmental noise. The paper presents novel as well as known speech and noise estimation techniques and combines them into a highly effective speech enhancement system. The algorithm is based on short-time spectral amplitude estimation, soft-decision gain modification, tracking of the a priori probability of speech absence, and minimum statistics noise power estimation. Special emphasis is placed on enhancing the performance of the preprocessor in nonstationary noise environments. Keywords and phrases: speech enhancement, noise reduction, speech coding, spectral analysis-synthesis, minimum statistics.
1.
INTRODUCTION
With the advent and wide dissemination of mobile voice communication systems, telephone conversations are increasingly disturbed by environmental noise. This is especially true in hands-free environments where the microphone is far away from the speech source. As a result, the quality and intelligibility of the transmitted speech can be significantly degraded and fail to meet the expectations of mobile phone users. The environmental noise problem becomes even more pronounced when low bit rate coders are used in harsh acoustic environments. An example is the mixed excitation linear prediction (MELP) coder which operates at bit rates of 1.2 and 2.4 kbps. It is used for secure governmental communications and has been selected as the future NATO narrow-band voice coder [1]. In contrast to waveform approximating coders, low bit rate coders transmit parameters of a speech production model instead of the quan-
tized acoustic waveform itself. Thus, low bit rate coders are more susceptible to a mismatch of the input signal and the underlying signal model. It is well known that single microphone speech enhancement algorithms improve the quality of noisy speech when the noise is fairly stationary. However, they typically do not improve the intelligibility when the enhanced signal is presented directly to a human listener. The loss of intelligibility is mostly a result of the distortions introduced into the speech signal by the noise reduction preprocessor. However
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