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1.
Two gain forms of spectral amplitude subtraction are derived theoretically without neglecting the correlation of speech and noise spectrum during the period of a fralne. In the implementation, the constrained gain is expressed as a function of noncausal a priori SNR (Signal-to-Noise Ratio). Noise and noncausal a priori SNR are estimated from the multitaper spectrum of the noisy signal with algorithms modified to be suitable for the multitaper spectruln. Objective evaluations show that in case of white Gaussian noise the proposed method outperforms some methods based on LSA (Log Spectral Amplitude) in terms of MBSD (Modified Bark Spectral Distortion), segmental SNR and overall SNR, and informal listening tests show that speech reconstructed in this way has little speech distortion and musical noise is nearly inaudible even at low SNR.  相似文献   

2.
基于最小统计量和掩蔽效应的单通道语音增强   总被引:4,自引:0,他引:4  
利用人耳感知的掩蔽特性,并结合含噪语音能量的最小统计量估计,提出了一种低信噪比下的单通道语音增强算法。该算法对原始语音在Bark频带能量的最小统计量进行估计,从而准确估计含噪语音信噪比,再从感知的角度,在时域和Bark频域上合理调整增强系数,以实现语音增强的目的。实验表明,该增强算法能够在减小语音失真的同时,很好地抑制背景噪声和残余音乐噪声。  相似文献   

3.
This article presents a new method for localization of multiple concurrent speech sources that relies on simultaneous blind signal separation and direction of arrival (DOA) estimation, as well as a method to solve the intersection point selection problem that arises when locating multiple speech sources using multiple sensor arrays. The proposed method is based on a low complexity non-parametric blind signal separation method, making is suitable for real-time applications on embedded platforms. On top of reduced complexity in comparison to a previously presented method, the DOA estimation accuracy is also improved. Evaluation of the performance is done with both real recording and simulations, and a real-time prototype of the proposed method has been implemented on a DSP platform to evaluate the computational and the memory complexities in a real application.  相似文献   

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