{"title":"Binaural multichannel Wiener filter with directional interference rejection","authors":"E. Hadad, Daniel Marquardt, S. Doclo, S. Gannot","doi":"10.1109/ICASSP.2015.7178048","DOIUrl":null,"url":null,"abstract":"In this paper we consider an acoustic scenario with a desired source and a directional interference picked up by hearing devices in a noisy and reverberant environment. We present an extension of the binaural multichannel Wiener filter (BMWF), by adding an interference rejection constraint to its cost function, in order to combine the advantages of spatial and spectral filtering while mitigating directional interferences. We prove that this algorithm can be decomposed into the binaural linearly constrained minimum variance (BLCMV) algorithm followed by a single channel Wiener post-filter. The proposed algorithm yields improved interference rejection capabilities, as compared with the BMWF. Moreover, by utilizing the spectral information on the sources, it is demonstrating better SNR measures, as compared with the BLCMV.","PeriodicalId":117666,"journal":{"name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2015.7178048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
In this paper we consider an acoustic scenario with a desired source and a directional interference picked up by hearing devices in a noisy and reverberant environment. We present an extension of the binaural multichannel Wiener filter (BMWF), by adding an interference rejection constraint to its cost function, in order to combine the advantages of spatial and spectral filtering while mitigating directional interferences. We prove that this algorithm can be decomposed into the binaural linearly constrained minimum variance (BLCMV) algorithm followed by a single channel Wiener post-filter. The proposed algorithm yields improved interference rejection capabilities, as compared with the BMWF. Moreover, by utilizing the spectral information on the sources, it is demonstrating better SNR measures, as compared with the BLCMV.