A Two-Sensor Noise Reduction System: Applications for Hands-Free Car Kit

Abstract

<p/> <p>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.</p

Two-Microphone Noise Reduction Using Spatial Information-Based Spectral Amplitude Estimation

“…From the above equations we can find that one of the important parts of noise estimation is P[H 1 |X,ΔΨ, Γ], which is a dual channel target presence probability estimator defined in (11). We will explain the details in the next section.…”

Real-Time Dual-Microphone Speech Enhancement

“…It was found that this method performs well in enhancing the signal-to-noise ratio (SNR) at the beamformer's output without introducing further distortion to the desired signal components (Guerin et al, 2003). However, the achievable noise reduction performance is limited by the amount of incoherent noise.…”

“…In this method, the cross-power spectral density of the two input signals was averaged during speech pauses and subtracted from the estimated CPSD in the presence of speech. In (Guerin et al, 2003), the authors have suggested an adaptive smoothing parameter estimator to determine the noise CPSD that should be used in the coherence-magnitude based filter. By evaluating the required overestimation for the noise CPSD, the authors showed that the musical noise (resulting from large fluctuations of the smoothing parameter between speech and non-speech periods) could be carefully controlled, especially during speech activity.…”

“…The CPSD-based approach (Zelinski, 1988(Zelinski, , 1990, the adaptive noise canceller (ANC) approach (Maj et al, 2006), (Berghe & Wooters, 1998), and the CSS-based approach (Guerin et al, 2003;Le Bouquin-Jannès et al, 1997;Zhang & Jia, 2005) are well-known examples. The former lacks robustness in a number of practical noise fields (i.e., coherent noise).…”

A Dual-Microphone Algorithm That Can Cope With Competing-Talker Scenarios

“…The coherence function has been investigated in many studies, such as [16]- [18], as a means for noise reduction and speech dereverberation. In all those studies the common assumption is that speech signals at the two microphones are highly correlated, while interfering signals are uncorrelated.…”