A Preliminary Case Study on Long-Form In-the-Wild Audio Spoofing Detection

Fuente: arXiv
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Main Authors: Liu, Xuechen, Wang, Xin, Yamagishi, Junichi
Format: Preprint
Published: 2024
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author Liu, Xuechen
Wang, Xin
Yamagishi, Junichi
author_facet Liu, Xuechen
Wang, Xin
Yamagishi, Junichi
contents Audio spoofing detection has become increasingly important due to the rise in real-world cases. Current spoofing detectors, referred to as spoofing countermeasures (CM), are mainly trained and focused on audio waveforms with a single speaker and short duration. This study explores spoofing detection in more realistic scenarios, where the audio is long in duration and features multiple speakers and complex acoustic conditions. We test the widely-acquired AASIST under this challenging scenario, looking at the impact of multiple variations such as duration, speaker presence, and acoustic complexities on CM performance. Our work reveals key issues with current methods and suggests preliminary ways to improve them. We aim to make spoofing detection more applicable in more in-the-wild scenarios. This research is served as an important step towards developing detection systems that can handle the challenges of audio spoofing in real-world applications.
format Preprint
id arxiv_https___arxiv_org_abs_2408_14066
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Preliminary Case Study on Long-Form In-the-Wild Audio Spoofing Detection
Liu, Xuechen
Wang, Xin
Yamagishi, Junichi
Sound
Cryptography and Security
Audio and Speech Processing
Audio spoofing detection has become increasingly important due to the rise in real-world cases. Current spoofing detectors, referred to as spoofing countermeasures (CM), are mainly trained and focused on audio waveforms with a single speaker and short duration. This study explores spoofing detection in more realistic scenarios, where the audio is long in duration and features multiple speakers and complex acoustic conditions. We test the widely-acquired AASIST under this challenging scenario, looking at the impact of multiple variations such as duration, speaker presence, and acoustic complexities on CM performance. Our work reveals key issues with current methods and suggests preliminary ways to improve them. We aim to make spoofing detection more applicable in more in-the-wild scenarios. This research is served as an important step towards developing detection systems that can handle the challenges of audio spoofing in real-world applications.
title A Preliminary Case Study on Long-Form In-the-Wild Audio Spoofing Detection
topic Sound
Cryptography and Security
Audio and Speech Processing
url https://arxiv.org/abs/2408.14066