Temporal Howling Detector for Speech Reinforcement Systems

IF 1.3 Q3 ACOUSTICS Acoustics (Basel, Switzerland) Pub Date : 2022-11-15 DOI:10.3390/acoustics4040060
Yehav Alkaher, I. Cohen
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引用次数: 2

Abstract

In this paper, we address the problem of howling detection in speech reinforcement system applications for utilization in howling control mechanisms. A general speech reinforcement system acquires speech from a speaker’s microphone, and delivers a reinforced speech to other listeners in the same room, or another room, through loudspeakers. The amount of gain that can be applied to the acquired speech in the closed-loop system is constrained by electro-acoustic coupling in the system, manifested in howling noises appearing as a result of acoustic feedback. A howling detection algorithm aims to early detect frequency-howls in the system, before the human ear notices. The proposed algorithm includes two cascaded stages: Soft Howling Detection and Howling False-Alarm Detection. The Soft Howling Detection is based on the temporal magnitude-slope-deviation measure, identifying potential candidate frequency-howls. Inspired by the temporal approach, the Howling False-Alarm Detection stage considers the understanding of speech-signal frequency components’ magnitude behavior under different levels of acoustic feedback. A comprehensive howling detection performance evaluation process is designed, examining the proposed algorithm in terms of detection accuracy and the time it takes for detection, under a devised set of howling scenarios. The performance improvement of the proposed algorithm, with respect to a plain magnitude-slope-deviation-based method, is demonstrated by showing faster detection response times over a set of howling change-rate configurations. The two-staged proposed algorithm also provides a significant recall improvement, while improving the precision decrease via the Howling False-Alarm Detection stage.
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语音强化系统的时间啸叫检测器
在本文中,我们解决了在语音增强系统中用于啸声控制机制的啸声检测问题。通用语音增强系统从扬声器的麦克风获取语音,并通过扬声器将增强的语音传递给同一房间或另一房间的其他听众。可应用于闭环系统中采集的语音的增益量受到系统中电声耦合的约束,表现为作为声反馈结果出现的啸声噪声。啸声检测算法旨在在人类耳朵注意到之前,早期检测系统中的频率啸声。该算法包括两个级联阶段:软啸叫检测和啸叫虚警检测。软啸叫检测基于时间幅度斜率偏差测量,识别潜在的候选频率啸叫。受时间方法的启发,Howling误报检测阶段考虑了对语音信号频率分量在不同声反馈水平下的幅度行为的理解。设计了一个全面的啸声检测性能评估过程,在设计的一组啸声场景下,从检测精度和检测所需时间方面检查了所提出的算法。通过在一组啸声变化率配置上显示更快的检测响应时间,证明了所提出的算法相对于基于平面幅度斜率偏差的方法的性能改进。所提出的两阶段算法也提供了显著的召回改进,同时通过Howling误报检测阶段改善了精度的降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.70
自引率
0.00%
发文量
0
审稿时长
11 weeks
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