FA-ExU-Net: The Simultaneous Training of an Embedding Extractor and Enhancement Model for a Speaker Verification System Robust to Short Noisy Utterances-Reference-Cited by-同舟云学术

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FA-ExU-Net: The Simultaneous Training of an Embedding Extractor and Enhancement Model for a Speaker Verification System Robust to Short Noisy Utterances

Published:2024 Issue: Volume:32 Page:2269-2282
ISSN:2329-9290
Container-title:IEEE/ACM Transactions on Audio, Speech, and Language Processing
language:
Short-container-title:IEEE/ACM Trans. Audio Speech Lang. Process.

Author:

Kim Ju-ho¹^ORCID,Heo Jungwoo¹^ORCID,Shin Hyun-seo¹^ORCID,Lim Chan-yeong¹^ORCID,Yu Ha-Jin¹^ORCID

Affiliation:

1. School of Computer Science, University of Seoul, Seoul, South Korea

Funder

2023 Research Fund of the University of Seoul

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6570655/10304349/10478124.pdf?arnumber=10478124

Reference81 articles.

1. A Tutorial on Text-Independent Speaker Verification

2. Deep Neural Network Embeddings for Text-Independent Speaker Verification

3. A Survey on Text-Dependent and Text-Independent Speaker Verification

4. Extended U-Net for Speaker Verification in Noisy Environments

5. RawNeXt: Speaker Verification System For Variable-Duration Utterances With Deep Layer Aggregation And Extended Dynamic Scaling Policies

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