Title :
A spectral subtraction algorithm for suppression of acoustic noise in speech
Author_Institution :
University of Utah, Salt Lake City, Utah
Abstract :
Spectral subtraction has been shown to be an effective approach for reducing ambient acoustic noise in order to improve the intelligibility and quality of digitally compressed speech. This paper presents a set of implementation specifications to improve algorithm performance and minimize algorithm computation and memory requirements. It is shown spectral subtraction can be implemented in terms of a nonstationary, multiplicative, frequency domain filter which changes with the time varying spectral characteristics of the speech. Using this filter a speech activity detector is defined and used to allow the algorithm to adapt automatically to changing ambient noise environments. Also the bandwidth information of this filter is used to further reduce the residual narrowband noise components which remain after spectral subtraction.
Keywords :
Acoustic noise; Bandwidth; Detectors; Frequency domain analysis; Information filtering; Information filters; Narrowband; Noise reduction; Speech enhancement; Working environment noise;
Conference_Titel :
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '79.
DOI :
10.1109/ICASSP.1979.1170696