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Harmonicity-Based Blind Dereverberation for Single-Channel Speech Signals

机译:单通道语音信号基于谐波的盲去混响

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The distant acquisition of acoustic signals in an enclosed space often produces reverberant artifacts due to the room impulse response. Speech dereverberation is desirable in situations where the distant acquisition of acoustic signals is involved. These situations include hands-free speech recognition, teleconferencing, and meeting recording, to name a few. This paper proposes a processing method, named Harmonicity-based dEReverBeration (HERB), to reduce the amount of reverberation in the signal picked up by a single microphone. The method makes extensive use of harmonicity, a unique characteristic of speech, in the design of a dereverberation filter. In particular, harmonicity enhancement is proposed and demonstrated as an effective way of estimating a filter that approximates an inverse filter corresponding to the room impulse response. Two specific harmonicity enhancement techniques are presented and compared; one based on an average transfer function and the other on the minimization of a mean squared error function. Prototype HERB systems are implemented by introducing several techniques to improve the accuracy of dereverberation filter estimation, including time warping analysis. Experimental results show that the proposed methods can achieve high-quality speech dereverberation, when the reverberation time is between 0.1 and 1.0 s, in terms of reverberation energy decay curves and automatic speech recognition accuracy
机译:由于房间的脉冲响应,在封闭空间中遥远地采集声信号常常会产生混响伪影。在涉及声信号的远距离采集的情况下,期望语音去混响。这些情况包括免提语音识别,电话会议和会议录音等。本文提出一种处理方法,称为基于谐波的dEReverBeration(HERB),以减少单个麦克风拾取的信号中的混响量。该方法在去混响滤波器的设计中广泛使用了谐波(语音的独特特征)。特别地,提出并证明了谐波增强作为估计滤波器的有效方式,该滤波器近似于对应于房间脉冲响应的逆滤波器。提出并比较了两种特定的谐波增强技术;一个基于平均传递函数,另一个基于最小均方误差函数。原型HERB系统是通过引入几种技术来实现的,以提高去混响滤波器估计的准确性,其中包括时间扭曲分析。实验结果表明,从混响能量衰减曲线和自动语音识别精度两方面来看,该方法在混响时间为0.1〜1.0 s之间均能实现高质量的语音混响。

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