SV - VLSP2021: The Smartcall - ITS’s Systems

Hung Van Dinh, Tuan Van Mai, Quyen B. Dam, Bao Quoc Nguyen
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Abstract

This paper presents the Smartcall - ITS’s systems submitted to the Vietnamese Language and Speech Processing, Speaker Verification (SV) task. The challenge consists of two tasks focusing on the development of SV models with limited data and testing the robustness of SV systems. In both tasks, we used various pre-trained speaker embedding models with different architectures: TDNN, Resnet34. After a specific fine-tuning strategy with data from the organiser, our system achieved the first rank for both two tasks with the Equal Error Rate respectively are 1.755%, 1.95%. In this paper, we describe our system developed for the booth two tasks in the VLSP2021 Speaker Verification shared-task.
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SV - VLSP2021: Smartcall - ITS的系统
本文介绍了智能呼叫ITS系统在越南语语言语音处理、说话人验证(SV)任务中的应用。挑战包括两项任务,重点是在有限数据下开发SV模型和测试SV系统的鲁棒性。在这两个任务中,我们使用了不同架构的各种预训练的说话人嵌入模型:TDNN, Resnet34。在使用组织者的数据进行特定的微调策略后,我们的系统在两个任务上都获得了第一名,错误率分别为1.755%和1.95%。在本文中,我们描述了我们在VLSP2021扬声器验证共享任务中为展台两个任务开发的系统。
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