THUEE system description for NIST 2020 SRE CTS challenge

10/12/2022
by   Yu Zheng, et al.
1

This paper presents the system description of the THUEE team for the NIST 2020 Speaker Recognition Evaluation (SRE) conversational telephone speech (CTS) challenge. The subsystems including ResNet74, ResNet152, and RepVGG-B2 are developed as speaker embedding extractors in this evaluation. We used combined AM-Softmax and AAM-Softmax based loss functions, namely CM-Softmax. We adopted a two-staged training strategy to further improve system performance. We fused all individual systems as our final submission. Our approach leads to excellent performance and ranks 1st in the challenge.

READ FULL TEXT

page 1

page 2

page 3

research
02/06/2021

The DKU-Duke-Lenovo System Description for the Third DIHARD Speech Diarization Challenge

In this paper, we present the submitted system for the third DIHARD Spee...
research
09/23/2022

The SpeakIn Speaker Verification System for Far-Field Speaker Verification Challenge 2022

This paper describes speaker verification (SV) systems submitted by the ...
research
09/08/2021

Beijing ZKJ-NPU Speaker Verification System for VoxCeleb Speaker Recognition Challenge 2021

In this report, we describe the Beijing ZKJ-NPU team submission to the V...
research
12/25/2019

THUEE system description for NIST 2019 SRE CTS Challenge

This paper describes the systems submitted by the department of electron...
research
09/22/2022

The SpeakIn System Description for CNSRC2022

This report describes our speaker verification systems for the tasks of ...
research
01/28/2019

Additive Margin SincNet for Speaker Recognition

Speaker Recognition is a challenging task with essential applications su...
research
10/11/2021

Multi-query multi-head attention pooling and Inter-topK penalty for speaker verification

This paper describes the multi-query multi-head attention (MQMHA) poolin...

Please sign up or login with your details

Forgot password? Click here to reset