整合产品频谱和伽玛通滤波器组用于噪声条件下的鲁棒扬声器验证

M. Fedila, Messaoud Bengherabi, A. Amrouche
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引用次数: 6

摘要

由于语音和音频处理领域的最新进展,结合相位信息可以进一步提高最先进的相位无关特征的性能。本文提出了一种改进Mel-frequency乘积谱倒谱系数(MFPSCC)提取管道的方法,该方法使用Mel- Scale滤波器组来扭曲乘积谱。这项工作的主要新颖之处在于将Gammatone滤波器组作为Mel滤波器组的替代品,以增强整个说话人验证系统在噪声条件下的鲁棒性。提出的特征被称为伽玛酮产品谱倒谱系数GPSCC。利用GMMUBM事实标准对受不同平稳和非平稳噪声干扰的TIMIT语料库进行了实验验证。性能评估表明,与其他相关特性相比,使用GPSCC可以显著降低相等错误率,而且在低信噪比下,这种性能增益更为明显。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Consolidating Product Spectrum and Gammatone filterbank for robust speaker verification under noisy conditions
Motivated by recent advances in speech and audio processing community reporting that incorporating the phase information can improve further the performance of state-of-the-art phase-independent features. We propose in this paper a modification in the extraction pipeline of the Mel-frequency Product Spectrum Cepstral Coefficients MFPSCC which warp the product spectrum with a Mel- Scale filterbank. The main novelty of this work resides in incorporating a Gammatone filterbank as a substitute of the Mel filterbank to reinforce the robustness of whole speaker verification system in noisy conditions. The proposed feature is dubbed the Gammatone Product-Spectrum Cepstral coefficients GPSCC. Experimental results are undertaken on the TIMIT corpus corrupted by different stationary and non-stationary noises using the GMMUBM de facto standard for speaker verification. Performance evaluations demonstrate drastic reduction in Equal Error Rates when using GPSCC compared to other related features and this gain in performance is more pronounced at low signal to noise ratios.
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