Unsupervised Speaker Verification Using Pre-Trained Model and Label Correction
Author:
Affiliation:
1. Xiamen University,School of Electronic Science and Engineering,China
2. Xiamen University,School of Informatics,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10094559/10094560/10094610.pdf?arnumber=10094610
Reference27 articles.
1. An Iterative Framework for Self-Supervised Deep Speaker Representation Learning
2. ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verification
3. Self-Supervised Speaker Recognition with Loss-Gated Learning
4. The DKU-DukeECE system for the self-supervision speaker verification task of the 2021 VoxCeleb speaker recognition challenge;cai,2021
5. Large-Scale Self-Supervised Speech Representation Learning for Automatic Speaker Verification
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1. SR-HuBERT : An Efficient Pre-Trained Model for Speaker Verification;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
2. Distance Metric-Based Open-Set Domain Adaptation for Speaker Verification;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024
3. Improving Speaker Verification With Noise-Aware Label Ensembling and Sample Selection: Learning and Correcting Noisy Speaker Labels;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024
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