{"title":"Low-order modeling of head-related transfer functions using wavelet transforms","authors":"J. Torres, M. R. Petraglia, R. Tenenbaum","doi":"10.1109/ISCAS.2004.1328796","DOIUrl":null,"url":null,"abstract":"In this paper, an efficient method for modeling head-related transfer functions (HRTFs) of an auralization system is presented. The proposed model is based on the decomposition of the impulse response of the HRTFs by wavelet transforms. Through an analysis of the HRTF energy content per subband it is shown how the model can be reduced without introducing considerable error in the magnitude and phase frequency responses. As a result of the proposed technique, the low-order model has approximately 30% of the number of coefficients of the original HRTF, which represents an important reduction in the computational cost of an auralization system implementation.","PeriodicalId":6445,"journal":{"name":"2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512)","volume":"142 1","pages":"III-513"},"PeriodicalIF":0.0000,"publicationDate":"2004-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAS.2004.1328796","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, an efficient method for modeling head-related transfer functions (HRTFs) of an auralization system is presented. The proposed model is based on the decomposition of the impulse response of the HRTFs by wavelet transforms. Through an analysis of the HRTF energy content per subband it is shown how the model can be reduced without introducing considerable error in the magnitude and phase frequency responses. As a result of the proposed technique, the low-order model has approximately 30% of the number of coefficients of the original HRTF, which represents an important reduction in the computational cost of an auralization system implementation.