{"title":"Dual-Microphone Speech Reinforcement System With Howling-Control for In-Car Speech Communication","authors":"Yehav Alkaher, Israel Cohen ","doi":"10.3389/frsip.2022.819113","DOIUrl":null,"url":null,"abstract":"In this paper, we address the problem of dual-microphone speech reinforcement for improving in-car speech communication via howling control. A speech reinforcement system acquires speech from a speaker’s microphone and delivers it to the other listeners in the car cabin through loudspeakers. A car cabin’s small space makes it vulnerable to acoustic feedback, resulting in the appearance of howling noises. The proposed system aims to maintain a desired high amplification gain over time while not compromising the output speech quality. The dual-microphone system consists of a microphone for speech acquisition and another microphone that monitors the environment for howling detection, where its location depends on its howling detection sensitivity. The proposed algorithm contains a gain-control segment based on the magnitude-slope-deviation measure, which reduces the amplification-gain in the case of howling detection. To find the optimal locations of the howling-detection microphone in the cabin, for a devised set of scenarios, a Pareto optimization method is applied. The Pareto optimization considers the bi-objective nature of the problem, i.e., minimizing both the relative gain-reduction and the overall speech distortion. It is shown that the proposed dual-microphone system outperforms a single-microphone-based system. The performance improvement is demonstrated by showing the higher howling detection sensitivity of the dual-microphone system. Additionally, a microphone constellation design process, for optimal howling detection, is provided through the utilization of the Pareto fronts and anti-fronts approach.","PeriodicalId":93557,"journal":{"name":"Frontiers in signal processing","volume":"87 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in signal processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/frsip.2022.819113","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, we address the problem of dual-microphone speech reinforcement for improving in-car speech communication via howling control. A speech reinforcement system acquires speech from a speaker’s microphone and delivers it to the other listeners in the car cabin through loudspeakers. A car cabin’s small space makes it vulnerable to acoustic feedback, resulting in the appearance of howling noises. The proposed system aims to maintain a desired high amplification gain over time while not compromising the output speech quality. The dual-microphone system consists of a microphone for speech acquisition and another microphone that monitors the environment for howling detection, where its location depends on its howling detection sensitivity. The proposed algorithm contains a gain-control segment based on the magnitude-slope-deviation measure, which reduces the amplification-gain in the case of howling detection. To find the optimal locations of the howling-detection microphone in the cabin, for a devised set of scenarios, a Pareto optimization method is applied. The Pareto optimization considers the bi-objective nature of the problem, i.e., minimizing both the relative gain-reduction and the overall speech distortion. It is shown that the proposed dual-microphone system outperforms a single-microphone-based system. The performance improvement is demonstrated by showing the higher howling detection sensitivity of the dual-microphone system. Additionally, a microphone constellation design process, for optimal howling detection, is provided through the utilization of the Pareto fronts and anti-fronts approach.