集成语音增强和编码技术

M. Kuropatwinski, D. Leckschat, K. Kroschel, A. Czyżewski
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引用次数: 5

摘要

低比特率合成分析线性预测编码器(LPAS编码器)中常用的语音编码技术可以作为语音信号模型,强调其重要特性。本文展示了如何利用这种编码方法进行语音增强。特别地,语音信号被建模为自适应形成峰滤波器和基音滤波器级联的输出,由方差随时间变化的高斯白过程驱动。研究了一种基于卡尔曼滤波的语音信号估计方法,实现了该语音信号模型。与仅使用短时语音参数的卡尔曼滤波方法相比,该方法在信噪比和主观印象方面都有显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integration of speech enhancement and coding techniques
Speech coding techniques commonly used in low bit rate analysis-by-synthesis linear predictive coders (LPAS coders) can serve as a speech signal model emphasizing its important features. In the paper it is shown how this coding method can be utilized for speech enhancement. Particularly, the speech signal is modeled as the output of a cascade of an adaptive formant filter and a pitch filter, driven by a white Gaussian process with variance changing with time. A signal estimation method based on the Kalman filter is investigated which implements this speech signal model. The proposed approach yields significantly better performance both in SNR and subjective impression than Kalman filter methods, which use only short-time speech parameters.
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