VLSP 2021 - SV challenge: Vietnamese Speaker Verification in Noisy Environments

Vi Thanh Dat, Phạm Việt Thành, Nguyen Thi Thu Trang
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引用次数: 4

Abstract

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.
VLSP 2021 - SV挑战:嘈杂环境下的越南语说话人验证
VLSP 2021是在胡志明市越南国立大学信息技术大学(unit - vnu - hcm)举办的第八届年度国际研讨会。这是我们第一次组织演讲者验证共享任务,分为两个子任务SV-T1和SV-T2。SV- t1侧重于开发有限数据的SV模型,SV- t2侧重于测试SV系统的能力和鲁棒性。为了促进鲁棒模型的发展,我们收集、处理并发布了一个嘈杂环境下的说话人数据集,其中包含50小时的语音和1300多个说话人身份。共有39支队伍报名参加了这个共享任务,15支队伍收到了数据集,最后,7支队伍提交了最终的解决方案。最佳解决方案利用英语预训练模型,SV-T1和SV-T2的相等错误率分别为1.755%和1.950%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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