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Effective noise reduction of speech signals using adaptive lattice filtering, segmentation and soft decision

机译:使用自适应晶格滤波,分段和软判决有效降低语音信号的噪声

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One major aspect of current research in speech processing, such as recognition and coding, is to develop systems which retain good performance across a wide variety of acoustic environments. The need for such systems is well appreciated. One method of making robust speech systems is to include a preprocessing stage of noise reduction. The challenge here is to reduce the noise level, preserve or improve the intelligibility and, at the same time, introduce as little distortion as possible. This is a very difficult task and a good solution is still to be found. The work presented here was inspired by previous research by the author in maximum noise reduction of noisy images using Karhunen-Loeve transform.
机译:当前语音处理研究(例如识别和编码)的一个主要方面是开发可在各种声学环境中保持良好性能的系统。人们对这样的系统的需求已广为人知。制作健壮的语音系统的一种方法是包括降噪的预处理阶段。这里的挑战是降低噪声水平,保持或提高清晰度,同时,尽可能减少失真。这是一项非常艰巨的任务,仍然有一个好的解决方案。本文介绍的工作受到作者先前的研究启发,该研究使用Karhunen-Loeve变换最大程度地减少了噪点图像的噪声。

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