Gradient Weighting for Speaker Verification in Extremely Low Signal-to-Noise Ratio-Reference-Cited by-同舟云学术

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Gradient Weighting for Speaker Verification in Extremely Low Signal-to-Noise Ratio

Published:2024-04-14 Issue: Volume:30 Page:11311-11315
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Ma Yi¹,Lee Kong Aik²,Hautamäki Ville³,Ge Meng¹,Li Haizhou⁴

Affiliation:

1. National University of Singapore,Department of Electrical and Computer Engineering,Singapore

2. The Hong Kong Polytechnic University,Department of Electrical and Electronic Engineering,Hong Kong

3. University of Eastern Finland,School of Computing,Finland

4. Shenzhen Research Institute of Big Data,Shenzhen,China

Funder

National Natural Science Foundation of China

Shenzhen Research Institute of Big Data

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10446174.pdf?arnumber=10446174

Reference29 articles.

1. VoiceID Loss: Speech Enhancement for Speaker Verification

2. Feature Enhancement with Deep Feature Losses for Speaker Verification

3. PL-EESR: Perceptual Loss Based End-to-End Robust Speaker Representation Extraction

4. Disentangling voice and content with self-supervision for speaker recognition;Liu

5. MFA: TDNN with Multi-Scale Frequency-Channel Attention for Text-Independent Speaker Verification with Short Utterances

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Developing a Low SNR Resistant, Text Independent Speaker Recognition System for Intercom Solutions - A Case Study;International Conference on Information Systems Development;2024-09-09

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