This paper presents a two-microphone speech enhancer designed to remove noise in hands-free car kits. The algorithm, based on the magnitude squared coherence, uses speech correlation and noise decorrelation to separate speech from noise. The remaining correlated noise is reduced using cross-spectral subtraction. Particular attention is focused on the estimation of the different spectral densities (noise and noisy signals power spectral densities) which are critical for the quality of the algorithm. We also propose a continuous noise estimation, avoiding the need of vocal activity detector. Results on recorded signals are provided, showing the superiority of the two-sensor approach to single microphone techniques.
CITATION STYLE
Guérin, A., Le Bouquin-Jeannès, R., & Faucon, G. (2003). A Two-Sensor Noise Reduction System: Applications for Hands-Free Car Kit. Eurasip Journal on Applied Signal Processing, 2003(11), 1125–1134. https://doi.org/10.1155/S1110865703305098
Mendeley helps you to discover research relevant for your work.