Title :
Gain adaptation based on signal-to-noise ratio for noise suppression
Author :
Parikh, Devangi N. ; Ravindran, Sourabh ; Anderson, David V.
Author_Institution :
Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
In this paper we describe a technique that uses adaptive gain control to achieve noise suppression in speech signals. The method used to map the dynamic range of the signal is based on the human auditory perceptual model. Since the processing is based on the model of human perception, the resulting noise suppressed speech is natural sounding. The computational complexity of the proposed method is low and the mapping of the dynamic range of the signal has a low delay. Because of these properties, this method is ideal for real-time implementation.
Keywords :
signal denoising; speech processing; adaptive gain control; computational complexity; gain adaptation; human auditory perceptual model; noise suppression; signal-to-noise ratio; speech processing; speech signals; Acoustic noise; Adaptive control; Computational complexity; Dynamic range; Gain control; Humans; Programmable control; Signal to noise ratio; Speech enhancement; Speech processing; Adaptive Gain; SNR; noise suppression; speech processing;
Conference_Titel :
Applications of Signal Processing to Audio and Acoustics, 2009. WASPAA '09. IEEE Workshop on
Conference_Location :
New Paltz, NY
Print_ISBN :
978-1-4244-3678-1
Electronic_ISBN :
1931-1168
DOI :
10.1109/ASPAA.2009.5346522