Spoofing-Robust Speaker Verification Using Parallel Embedding Fusion: BTU Speech Group's Approach for ASVspoof5 Challenge

Fuente: arXiv
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Autori principali: Kurnaz, Oğuzhan, Demirtaş, Selim Can, Büker, Aykut, Mishra, Jagabandhu, Hanilçi, Cemal
Natura: Preprint
Pubblicazione: 2024
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author Kurnaz, Oğuzhan
Demirtaş, Selim Can
Büker, Aykut
Mishra, Jagabandhu
Hanilçi, Cemal
author_facet Kurnaz, Oğuzhan
Demirtaş, Selim Can
Büker, Aykut
Mishra, Jagabandhu
Hanilçi, Cemal
contents This paper introduces the parallel network-based spoofing-aware speaker verification (SASV) system developed by BTU Speech Group for the ASVspoof5 Challenge. The SASV system integrates ASV and CM systems to enhance security against spoofing attacks. Our approach employs score and embedding fusion from ASV models (ECAPA-TDNN, WavLM) and CM models (AASIST). The fused embeddings are processed using a simple DNN structure, optimizing model performance with a combination of recently proposed a-DCF and BCE losses. We introduce a novel parallel network structure where two identical DNNs, fed with different inputs, independently process embeddings and produce SASV scores. The final SASV probability is derived by averaging these scores, enhancing robustness and accuracy. Experimental results demonstrate that the proposed parallel DNN structure outperforms traditional single DNN methods, offering a more reliable and secure speaker verification system against spoofing attacks.
format Preprint
id arxiv_https___arxiv_org_abs_2408_15877
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Spoofing-Robust Speaker Verification Using Parallel Embedding Fusion: BTU Speech Group's Approach for ASVspoof5 Challenge
Kurnaz, Oğuzhan
Demirtaş, Selim Can
Büker, Aykut
Mishra, Jagabandhu
Hanilçi, Cemal
Audio and Speech Processing
Sound
This paper introduces the parallel network-based spoofing-aware speaker verification (SASV) system developed by BTU Speech Group for the ASVspoof5 Challenge. The SASV system integrates ASV and CM systems to enhance security against spoofing attacks. Our approach employs score and embedding fusion from ASV models (ECAPA-TDNN, WavLM) and CM models (AASIST). The fused embeddings are processed using a simple DNN structure, optimizing model performance with a combination of recently proposed a-DCF and BCE losses. We introduce a novel parallel network structure where two identical DNNs, fed with different inputs, independently process embeddings and produce SASV scores. The final SASV probability is derived by averaging these scores, enhancing robustness and accuracy. Experimental results demonstrate that the proposed parallel DNN structure outperforms traditional single DNN methods, offering a more reliable and secure speaker verification system against spoofing attacks.
title Spoofing-Robust Speaker Verification Using Parallel Embedding Fusion: BTU Speech Group's Approach for ASVspoof5 Challenge
topic Audio and Speech Processing
Sound
url https://arxiv.org/abs/2408.15877