{"title":"基于矢量量化和隐马尔可夫模型的说话人验证","authors":"M. Z. Ilyas, S. Samad, A. Hussain, K. A. Ishak","doi":"10.1109/SCORED.2007.4451419","DOIUrl":null,"url":null,"abstract":"This paper presents a speaker verification system using a combination of vector quantization (VQ) and hidden Markov model (HMM) to improve the HMM performance. A Malay spoken digit database which contains 100 speakers is used for the testing and validation modules. It is shown that, by using the proposed combination technique, a total success rate (TSR) of 99.97% is achieved and it is an improvement of 11.24% in performance compared to HMM. For speaker verification, true speaker rejection rate, impostor acceptance rate and equal error rate (EER) are also improved significantly compared to HMM.","PeriodicalId":443652,"journal":{"name":"2007 5th Student Conference on Research and Development","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Speaker Verification using Vector Quantization and Hidden Markov Model\",\"authors\":\"M. Z. Ilyas, S. Samad, A. Hussain, K. A. Ishak\",\"doi\":\"10.1109/SCORED.2007.4451419\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a speaker verification system using a combination of vector quantization (VQ) and hidden Markov model (HMM) to improve the HMM performance. A Malay spoken digit database which contains 100 speakers is used for the testing and validation modules. It is shown that, by using the proposed combination technique, a total success rate (TSR) of 99.97% is achieved and it is an improvement of 11.24% in performance compared to HMM. For speaker verification, true speaker rejection rate, impostor acceptance rate and equal error rate (EER) are also improved significantly compared to HMM.\",\"PeriodicalId\":443652,\"journal\":{\"name\":\"2007 5th Student Conference on Research and Development\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 5th Student Conference on Research and Development\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCORED.2007.4451419\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 5th Student Conference on Research and Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCORED.2007.4451419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Speaker Verification using Vector Quantization and Hidden Markov Model
This paper presents a speaker verification system using a combination of vector quantization (VQ) and hidden Markov model (HMM) to improve the HMM performance. A Malay spoken digit database which contains 100 speakers is used for the testing and validation modules. It is shown that, by using the proposed combination technique, a total success rate (TSR) of 99.97% is achieved and it is an improvement of 11.24% in performance compared to HMM. For speaker verification, true speaker rejection rate, impostor acceptance rate and equal error rate (EER) are also improved significantly compared to HMM.
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