{"title":"四种距离度量在长时间文本无关说话人识别中的比较","authors":"S. Ong, S. Sridharan, Cheng-Hong Yang, M. Moody","doi":"10.1109/ISSPA.1996.615758","DOIUrl":null,"url":null,"abstract":"In this study, four distance measures were compared for text-independent speaker identitication using the long time statistical feature averaging method. The four methods were the City block, the Euclidean, the Weighted Euclidean, and the Mahalanobis distance measures. Identification decision was based on the minimum distance criterion. This study showed that the Weighted Euclidean distance measure performed best, and the Mahalanobis distance measure did not perform well. An explanation is advanced for this result.","PeriodicalId":359344,"journal":{"name":"Fourth International Symposium on Signal Processing and Its Applications","volume":"480 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Comparison of Four Distance Measures for Long Time Text-Independent Speaker Identification\",\"authors\":\"S. Ong, S. Sridharan, Cheng-Hong Yang, M. Moody\",\"doi\":\"10.1109/ISSPA.1996.615758\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, four distance measures were compared for text-independent speaker identitication using the long time statistical feature averaging method. The four methods were the City block, the Euclidean, the Weighted Euclidean, and the Mahalanobis distance measures. Identification decision was based on the minimum distance criterion. This study showed that the Weighted Euclidean distance measure performed best, and the Mahalanobis distance measure did not perform well. An explanation is advanced for this result.\",\"PeriodicalId\":359344,\"journal\":{\"name\":\"Fourth International Symposium on Signal Processing and Its Applications\",\"volume\":\"480 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fourth International Symposium on Signal Processing and Its Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSPA.1996.615758\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fourth International Symposium on Signal Processing and Its Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPA.1996.615758","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of Four Distance Measures for Long Time Text-Independent Speaker Identification
In this study, four distance measures were compared for text-independent speaker identitication using the long time statistical feature averaging method. The four methods were the City block, the Euclidean, the Weighted Euclidean, and the Mahalanobis distance measures. Identification decision was based on the minimum distance criterion. This study showed that the Weighted Euclidean distance measure performed best, and the Mahalanobis distance measure did not perform well. An explanation is advanced for this result.