结合人类听觉特性的信号子空间语音增强方法

F. Jabloun, B. Champagne
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引用次数: 189

摘要

在语音应用中,大多数降噪方法的主要缺点是恼人的残余噪声,即音乐噪声。一个潜在的解决方案是在抑制滤波器设计中加入人类听觉模型。然而,由于可用的模型通常是在频域中开发的,因此如何将它们应用于语音增强的信号子空间方法尚不清楚。在本文中,我们提出了一个频率到特征域变换(FET),它允许计算一个基于感知的特征滤波器。从感知的角度来看,该滤波器产生了更好的残余噪声整形的改进结果。该方法也适用于一般情况下的有色噪声。给出了频谱图图解和听力测试结果,表明了该方法相对于传统的信号子空间方法的优越性。
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Incorporating the human hearing properties in the signal subspace approach for speech enhancement
The major drawback of most noise reduction methods in speech applications is the annoying residual noise known as musical noise. A potential solution to this artifact is the incorporation of a human hearing model in the suppression filter design. However, since the available models are usually developed in the frequency domain, it is not clear how they can be applied in the signal subspace approach for speech enhancement. In this paper, we present a Frequency to Eigendomain Transformation (FET) which permits to calculate a perceptually based eigenfilter. This filter yields an improved result where better shaping of the residual noise, from a perceptual perspective, is achieved. The proposed method can also be used with the general case of colored noise. Spectrogram illustrations and listening test results are given to show the superiority of the proposed method over the conventional signal subspace approach.
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Errata to "Using Steady-State Suppression to Improve Speech Intelligibility in Reverberant Environments for Elderly Listeners" Farewell Editorial Inaugural Editorial: Riding the Tidal Wave of Human-Centric Information Processing - Innovate, Outreach, Collaborate, Connect, Expand, and Win Three-Dimensional Sound Field Reproduction Using Multiple Circular Loudspeaker Arrays Introduction to the Special Issue on Processing Reverberant Speech: Methodologies and Applications
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