Abstract
Speech enhancement has an increasing demand in mobile communications and faces a great challenge in a real ambient noisy environment. This paper develops an effective spatial-frequency domain speech enhancement method with a single acoustic vector sensor (AVS) in conjunction with minimum variance distortionless response (MVDR) spatial filtering and Wiener post-filtering (WPF) techniques. In remote speech applications, the MVDR spatial filtering is effective in suppressing the strong spatial interferences and the Wiener post-filtering is considered as a popular and powerful estimator to further suppress the residual noise if the power spectral density (PSD) of target speech can be estimated properly. With the favorable directional response of the AVS together with the trigonometric relations of the steering vectors, the closed-form estimation of the signal PSDs is derived and the frequency response of the optimal Wiener post-filter is determined accordingly. Extensive computer simulations and a real experiment in an anechoic chamber condition have been carried out to evaluate the performance of the proposed algorithm. Simulation results show that the proposed method offers good ability to suppress the spatial interference while maintaining comparable log spectral deviation and perceptual evaluation of speech quality performance compared with the conventional methods with several objective measures. Moreover, a single AVS solution is particularly attractive for hands-free speech applications due to its compact size.
Highlights
As the presence of background noise significantly deteriorates the quality and intelligibility of speech, enhancement of speech signals has been an important and challenging problem and various methods have been proposed in the literature to tackle this problem
The integrated minimum variance distortionless response (MVDR) and Wiener post-filtering method using acoustic vector sensor (AVS) array [12] offers good performance in terms of suppression of spatial interferences and background additive noise, but it requires more than two AVS units as well as the good voice activity detection (VAD) technique
6 Conclusions In this paper, a novel speech enhancement algorithm named as norm-constrained FMV (NCFMV)-EWPF has been derived with a single AVS unit by an efficient closed-form estimation of the power spectral densities of signals
Summary
As the presence of background noise significantly deteriorates the quality and intelligibility of speech, enhancement of speech signals has been an important and challenging problem and various methods have been proposed in the literature to tackle this problem. Using AVS array [12] offers good performance in terms of suppression of spatial interferences and background additive noise, but it requires more than two AVS units as well as the good voice activity detection (VAD) technique. We focus on developing a speech enhancement solution capable of effectively suppressing spatial interferences and additive noise at a less computational cost using only one AVS unit. The norm-constrained MVDR method is employed to form the spatial filter, while the optimal Wiener post-filter is designed by using a novel closed-form power spectral density (PSD) estimation method.
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