{"title":"基于相关维数的改进混响环境下的声源定位","authors":"Xinwang Wan, Zhen-yang Wu","doi":"10.1109/WCSP.2009.5371584","DOIUrl":null,"url":null,"abstract":"Speech source location estimation in a noisy, reverberant environment has attracted much attention recently. It was found that the localization method through calculating the steered response power (SRP) is more robust than time-difference-of-arrival (TDOA)-based localization method. The method places equal emphasis on each microphone pair in calculation of the SRP. In a room, each microphone is usually differently affected by noise and reverberation. Thus the performance of the SRP-based localization method will degrade. In this paper, we place a weighting on each microphone pair according to their correlation dimensions to compute SRP. Simulations show that the proposed correlation-dimension-based source localization method is more robust to noise and reverberation than the SRP-PHAT (phase transform) algorithm","PeriodicalId":244652,"journal":{"name":"2009 International Conference on Wireless Communications & Signal Processing","volume":"2 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improved speech source localization in reverberant environments based on correlation dimension\",\"authors\":\"Xinwang Wan, Zhen-yang Wu\",\"doi\":\"10.1109/WCSP.2009.5371584\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Speech source location estimation in a noisy, reverberant environment has attracted much attention recently. It was found that the localization method through calculating the steered response power (SRP) is more robust than time-difference-of-arrival (TDOA)-based localization method. The method places equal emphasis on each microphone pair in calculation of the SRP. In a room, each microphone is usually differently affected by noise and reverberation. Thus the performance of the SRP-based localization method will degrade. In this paper, we place a weighting on each microphone pair according to their correlation dimensions to compute SRP. Simulations show that the proposed correlation-dimension-based source localization method is more robust to noise and reverberation than the SRP-PHAT (phase transform) algorithm\",\"PeriodicalId\":244652,\"journal\":{\"name\":\"2009 International Conference on Wireless Communications & Signal Processing\",\"volume\":\"2 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Wireless Communications & Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCSP.2009.5371584\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Wireless Communications & Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCSP.2009.5371584","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improved speech source localization in reverberant environments based on correlation dimension
Speech source location estimation in a noisy, reverberant environment has attracted much attention recently. It was found that the localization method through calculating the steered response power (SRP) is more robust than time-difference-of-arrival (TDOA)-based localization method. The method places equal emphasis on each microphone pair in calculation of the SRP. In a room, each microphone is usually differently affected by noise and reverberation. Thus the performance of the SRP-based localization method will degrade. In this paper, we place a weighting on each microphone pair according to their correlation dimensions to compute SRP. Simulations show that the proposed correlation-dimension-based source localization method is more robust to noise and reverberation than the SRP-PHAT (phase transform) algorithm