{"title":"Local relative transfer function for sound source localization","authors":"Xiaofei Li, R. Horaud, Laurent Girin, S. Gannot","doi":"10.1109/EUSIPCO.2015.7362413","DOIUrl":null,"url":null,"abstract":"The relative transfer function (RTF), i.e. the ratio of acoustic transfer functions between two sensors, can be used for sound' source localization / beamforming based on a microphone array. The RTF is usually defined with respect to a unique reference sensor. Choosing the reference sensor may be a difficult task, especially for dynamic acoustic environment and setup. In this paper we propose to use a locally normalized RTF, in short local-RTF, as an acoustic feature to characterize the source direction. Local-RTF takes a neighbor sensor as the reference channel for a given sensor. The estimated local-RTF vector can thus avoid the bad effects of a noisy unique reference and have smaller estimation error than conventional RTF estimators. We propose two estimators for the local-RTF and concatenate the values across sensors and frequencies to form a high-dimensional vector which is utilized for source localization. Experiments with real-world signals show the interest of this approach.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 23rd European Signal Processing Conference (EUSIPCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EUSIPCO.2015.7362413","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
The relative transfer function (RTF), i.e. the ratio of acoustic transfer functions between two sensors, can be used for sound' source localization / beamforming based on a microphone array. The RTF is usually defined with respect to a unique reference sensor. Choosing the reference sensor may be a difficult task, especially for dynamic acoustic environment and setup. In this paper we propose to use a locally normalized RTF, in short local-RTF, as an acoustic feature to characterize the source direction. Local-RTF takes a neighbor sensor as the reference channel for a given sensor. The estimated local-RTF vector can thus avoid the bad effects of a noisy unique reference and have smaller estimation error than conventional RTF estimators. We propose two estimators for the local-RTF and concatenate the values across sensors and frequencies to form a high-dimensional vector which is utilized for source localization. Experiments with real-world signals show the interest of this approach.