噪声和混响环境下一种新的时延估计方法

Da-wei Zhang, C. Bao, Biny-yin Xia
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引用次数: 0

摘要

为了提高噪声和混响环境下的信号源定位性能,提出了一种新的时延估计方法。这种方法被称为基于统计模型的声传递函数比(ATFR-SM)。本算法采用基于统计模型的降噪方法来降低噪声对声传递函数(ATF)的影响。在ATF方法中,功率谱密度(PSD)被白化以减少混响的影响。语音活动检测(Voice Activity Detection, VAD)用于区分语音周期和噪声周期,并在语音周期内进行TDE以提高估计精度。性能评价结果表明,在噪声和混响条件下,与参考方法相比,该方法具有更低的异常点百分比(PAP)和更低的均方根误差(RMSE)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel Time Delay Estimation method in noisy and reverberant environments
In order to improve the performance of source localization in noisy and reverberant environments, a novel Time Delay Estimation (TDE) method is proposed in this paper. This method is called Acoustical Transfer Function Ratio based on Statistical Model (ATFR-SM). In our algorithm, the noise reduction method based on the statistical model is adopted to reduce the effect of noise on Acoustical Transfer Function (ATF). In the ATF method, the Power Spectral Density (PSD) is whitened to reduce the effect of reverberations. Voice Activity Detection (VAD) is used to distinguish the speech period from the noise period, and the TDE is performed in the speech period to improve the estimation accuracy. The results of performance evaluation show that, in both the noisy and reverberant conditions, the lower Percentage of Abnormal Points (PAP) and lower Root Mean Square Error (RMSE) can be achieved by the proposed method than the reference methods.
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