Vi Thanh Dat, Phạm Việt Thành, Nguyen Thi Thu Trang
{"title":"VLSP 2021 - SV挑战:嘈杂环境下的越南语说话人验证","authors":"Vi Thanh Dat, Phạm Việt Thành, Nguyen Thi Thu Trang","doi":"10.25073/2588-1086/vnucsce.333","DOIUrl":null,"url":null,"abstract":"\n \n \n \n \n \nThe VLSP 2021 is the eighth annual international workshop whose campaign was organized at the University of Information Technology, Vietnam National University, Ho Chi Minh City (UIT-VNU-HCM). This was the first time we organized the Speaker Verification shared task with two subtasks SV-T1 and SV-T2. SV-T1 focuses on the development of SV models with limited data, and SV-T2 focuses on testing the capability and the robustness of SV systems. With the aim to boost the development of robust models, we collected, processed, and published a speaker dataset in noisy environments containing 50 hours of speech and more than 1,300 speaker identities. A total of 39 teams registered to participate in this shared task, 15 teams received the dataset, and finally, 7 teams submitted final solutions. The best solution leveraged English pre-trained models and achieved 1.755% and 1.950% Equal Error Rate for SV-T1 and SV-T2 respectively. \n \n \n \n \n \n","PeriodicalId":416488,"journal":{"name":"VNU Journal of Science: Computer Science and Communication Engineering","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"VLSP 2021 - SV challenge: Vietnamese Speaker Verification in Noisy Environments\",\"authors\":\"Vi Thanh Dat, Phạm Việt Thành, Nguyen Thi Thu Trang\",\"doi\":\"10.25073/2588-1086/vnucsce.333\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n \\n \\n \\n \\nThe VLSP 2021 is the eighth annual international workshop whose campaign was organized at the University of Information Technology, Vietnam National University, Ho Chi Minh City (UIT-VNU-HCM). This was the first time we organized the Speaker Verification shared task with two subtasks SV-T1 and SV-T2. SV-T1 focuses on the development of SV models with limited data, and SV-T2 focuses on testing the capability and the robustness of SV systems. With the aim to boost the development of robust models, we collected, processed, and published a speaker dataset in noisy environments containing 50 hours of speech and more than 1,300 speaker identities. A total of 39 teams registered to participate in this shared task, 15 teams received the dataset, and finally, 7 teams submitted final solutions. The best solution leveraged English pre-trained models and achieved 1.755% and 1.950% Equal Error Rate for SV-T1 and SV-T2 respectively. \\n \\n \\n \\n \\n \\n\",\"PeriodicalId\":416488,\"journal\":{\"name\":\"VNU Journal of Science: Computer Science and Communication Engineering\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"VNU Journal of Science: Computer Science and Communication Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25073/2588-1086/vnucsce.333\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"VNU Journal of Science: Computer Science and Communication Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25073/2588-1086/vnucsce.333","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The VLSP 2021 is the eighth annual international workshop whose campaign was organized at the University of Information Technology, Vietnam National University, Ho Chi Minh City (UIT-VNU-HCM). This was the first time we organized the Speaker Verification shared task with two subtasks SV-T1 and SV-T2. SV-T1 focuses on the development of SV models with limited data, and SV-T2 focuses on testing the capability and the robustness of SV systems. With the aim to boost the development of robust models, we collected, processed, and published a speaker dataset in noisy environments containing 50 hours of speech and more than 1,300 speaker identities. A total of 39 teams registered to participate in this shared task, 15 teams received the dataset, and finally, 7 teams submitted final solutions. The best solution leveraged English pre-trained models and achieved 1.755% and 1.950% Equal Error Rate for SV-T1 and SV-T2 respectively.