A master thesis from Aalborg University
Among us - Detecting spoofed audio samples in a multi-party conversation -
Author(s)
Term
4. semester
Education
Publication year
2025
Submitted on
2025-06-03
Pages
78 pages
Abstract
As voice technologies become more preva- lent, it becomes vital to improve spoofing detection algorithms especially when mul- tiple speakers are involved. This thesis presents a novel pipeline combining speech separation with spoof detection to address the challenge of identifying spoofed audio samples in overlapped speech. The system uses a SOTA spoof detection model which achieves an EER of 2% on ASVspoof 2019 dataset. However, the EER drops to 24% when tested on a custom- generated mixed audio dataset, as a result of modifications of the audio artifacts by the speech separa- tion process. The system when trained on the custom dataset saw an increase in EER to 22% highlighting the importance of do- main adaptation for spoof detection in com- plex acoustic environments and provides a foundation for future research in real-world scenarios.
Documents
Colophon: This page is part of the AAU Student Projects portal, which is run by Aalborg University. Here, you can find and download publicly available bachelor's theses and master's projects from across the university dating from 2008 onwards. Student projects from before 2008 are available in printed form at Aalborg University Library.
If you have any questions about AAU Student Projects or the research registration, dissemination and analysis at Aalborg University, please feel free to contact the VBN team. You can also find more information in the AAU Student Projects FAQs.