{"title":"Robust acoustic speaker localization with distributed microphones","authors":"F. Hummes, Junge Qi, T. Fingscheidt","doi":"10.5281/ZENODO.42457","DOIUrl":null,"url":null,"abstract":"This contribution to acoustic source localization presents a robust approach verified with ten distributed microphones in a laboratory apartment under reverberant acoustic conditions. Based on the classical steered response power phase transform (SRP-PHAT) algorithm, three optional extensions are presented: A method for selecting suitable microphone pairs, a spatial Wiener-type filtering for the suppression of artifacts in the spatial likelihood function (stemming from background noise), and finally smoothing of the spatial likelihood function. Simulation results show a significant improvement compared to SRP-PHAT in all noise conditions.","PeriodicalId":331889,"journal":{"name":"2011 19th European Signal Processing Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 19th European Signal Processing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/ZENODO.42457","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
This contribution to acoustic source localization presents a robust approach verified with ten distributed microphones in a laboratory apartment under reverberant acoustic conditions. Based on the classical steered response power phase transform (SRP-PHAT) algorithm, three optional extensions are presented: A method for selecting suitable microphone pairs, a spatial Wiener-type filtering for the suppression of artifacts in the spatial likelihood function (stemming from background noise), and finally smoothing of the spatial likelihood function. Simulation results show a significant improvement compared to SRP-PHAT in all noise conditions.