An auditory perception based improved multi-band spectral subtraction algorithm for enhancement of speech degraded by non-stationary noises

Navneet Upadhyay, A. Karmakar
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引用次数: 1

Abstract

In this paper, an auditory perception based improved multi-band spectral subtraction algorithm is proposed to enhance the speech signal degraded by non-stationary or colored noises. In the proposed scheme, the whole speech spectrum is divided in different non-uniform bands (N = 6) in accordance to the critical-band rate scale and spectral subtraction is applied separately in each band. The proposed algorithm uses a new approach to estimate the noise power from each band without the need of explicit speech silence detection. The noise estimate is updated by adaptively smoothing the noisy signal power. The smoothing parameter is controlled by a linear function of a-posteriori signal-to-noise ratio (SNR). This noise estimation approach gives accurate results at low SNR and works continuously in the presence of speech. The objective measures as well as informal subjective tests demonstrate that the proposed algorithm reduces remnant noise efficiently and the enhanced speech contains minimal speech distortions with improved SNR.
一种基于听觉感知的改进多频带谱减法算法用于非平稳噪声语音的增强
本文提出了一种基于听觉感知的改进多频带谱减法算法,用于增强被非平稳噪声或有色噪声退化的语音信号。在该方案中,将整个语音频谱按照临界频带速率尺度划分为不同的非均匀频带(N = 6),并在每个频带分别进行频谱减法处理。该算法采用了一种新的方法来估计每个频带的噪声功率,而不需要明确的语音沉默检测。通过自适应平滑噪声信号功率来更新噪声估计。平滑参数由后验信噪比(SNR)的线性函数控制。这种噪声估计方法在低信噪比条件下能得到准确的结果,并且在有语音存在的情况下能连续工作。客观测量和非正式主观测试表明,该算法有效地降低了残余噪声,增强语音包含最小的语音失真,提高了信噪比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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