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Spatio-temporal filtering methods for enhancement and separation of speech signals

机译:用于增强和分离语音信号的时空滤波方法

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In this paper, we give an overview of the background for, the ideas behind, and the challenges to be addressed in the project 'Spatio-Temporal Filtering Methods for Enhancement and Separation of Speech Signals,' which is funded by the Villum Foundation. The project aims at addressing the problem of enhancing and separating speech signals from noisy mixtures, a problem also known as the cocktail party problem. It aims at exploring new ways of solving this problem by generalizing a new class of optimal temporal filtering methods for periodic signals to multiple microphones, resulting in so-called spatio-temporal filtering methods that are controlled by two parameters, the direction-of-arrival and the fundamental frequency. These filters are optimal in that they let the signal of interest pass undistorted while everything else is attenuated as much as possible. Unlike state-of-the-art methods, they do not require knowledge of the statistics of noise and interfering speech signals, something that is especially important when dealing with non-stationary noise.
机译:在本文中,我们概述了由Villum基金会资助的项目“时空滤波方法以增强和分离语音信号”的背景,背后的想法以及要解决的挑战。该项目旨在解决从嘈杂的混合信号中增强和分离语音信号的问题,也称为鸡尾酒会问题。它旨在通过针对到多个麦克风的周期信号推广一类新型的最佳时间滤波方法来探索解决此问题的新方法,从而产生由两个参数控制的所谓时空滤波方法,即到达方向和基本频率。这些滤波器是最佳的,因为它们可使感兴趣的信号不失真地通过,而其他所有信号则尽可能地衰减。与最新方法不同,它们不需要了解噪声和干扰语音信号的统计信息,这在处理非平稳噪声时尤其重要。

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