Shaghayegh Reza, Tahereh Emami Azadi, J. Kabudian, Y. Shekofteh
{"title":"A robust speaker recognition system combining factor analysis techniques","authors":"Shaghayegh Reza, Tahereh Emami Azadi, J. Kabudian, Y. Shekofteh","doi":"10.1109/ICBME.2014.7043948","DOIUrl":null,"url":null,"abstract":"In this paper we implement state of the art factor analysis based methods and fused their scores to gain a channel robust speaker recognition system. These two methods are joint factor analysis (JFA) and i-Vector which define low-dimensional speaker and channel dependent spaces. For score fusion we propose a simple weight computation without training step. We experiment our method on two conditions; 1) in channel matched training and test channel (telephone in training phase/telephone in test phase) task and 2) the channel mismatched condition (telephone training phase/microphone, GSM and VOIP in test phase) task. Our strategies outperform a state-of-the-art GMM-UBM based system. We obtained more than 4% absolute EER improvement for both channel dependent and channel independent condition compared to the standard GMM-UBM based method. Simulation also results that the combined system based on i-Vector and JFA gives better performance than all implemented method.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBME.2014.7043948","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper we implement state of the art factor analysis based methods and fused their scores to gain a channel robust speaker recognition system. These two methods are joint factor analysis (JFA) and i-Vector which define low-dimensional speaker and channel dependent spaces. For score fusion we propose a simple weight computation without training step. We experiment our method on two conditions; 1) in channel matched training and test channel (telephone in training phase/telephone in test phase) task and 2) the channel mismatched condition (telephone training phase/microphone, GSM and VOIP in test phase) task. Our strategies outperform a state-of-the-art GMM-UBM based system. We obtained more than 4% absolute EER improvement for both channel dependent and channel independent condition compared to the standard GMM-UBM based method. Simulation also results that the combined system based on i-Vector and JFA gives better performance than all implemented method.