Special issue on Advances in Automatic Speaker Verification Anti-spoofing
• 大类 : 工程技术 - 3区
• 小类 : 计算机：人工智能 - 4区
The performance of voice biometrics systems based on automatic speaker verification (ASV) technology degrades significantly in the presence of spoofing attacks. Over the past few years considerable progress has been made in the field of ASV anti-spoofing. This includes the development of new speech corpora, common evaluation protocols and advancements in front-end feature extraction and back-end classifiers. The ASVspoof initiative was launched to promote the development of countermeasures which aim to protect ASV from spoofing attacks. ASVspoof 2015, the first edition, focused on the detection of synthetic speech created with voice conversion (VC) and text-to-speech (TTS) methods. The second edition, ASVspoof 2017, focused on the detection of replayed speech.
ASVspoof 2019, the latest edition included two sub-challenges geared towards "logical access" (LA) and "physical access" (PA) scenarios. The LA scenario relates to the detection of synthetic speech created with advanced VC and TTS methods developed by academic and non-academic organizations. The PA scenario promotes the develop of countermeasures for the detection of replayed speech signals. More than 60 academic and industrial teams participated in the ASVspoof 2019 challenge. Preliminary results indicate considerable performance improvements in terms of two evaluation metrics adopted for the challenge. The top-ranking teams applied different machine learning algorithms suitable for the discrimination of natural and spoofed speech.
This special issue will feature articles describing top-performing techniques and detailed analyses of some of the systems reported in recent years by leading anti-spoofing researchers. The special issue will also consist of an overview article which covers ASVspoof 2019 challenge results, and meta analyses. The scope of the special issue is, however, not limited to work performed using the ASVspoof challenge datasets; studies conducted with other datasets are also welcome.
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Topics of interest include (but are not limited to):
Speaker verification anti-spoofing on ASVspoof 2019
Datasets for speaker verification anti-spoofing
Deep learning for spoofing and anti-spoofing
Joint evaluation of countermeasures and speaker verification
Evaluation methodology for speaker verification anti-spoofing
Voice conversion for spoofing speaker verification systems
Text-to-speech for spoofing speaker verification systems
Robust spoofing countermeasures
Generalized spoofing countermeasures
Audio watermarking for spoofing countermeasures
Acoustic fingerprinting for spoofing countermeasures
Knowledge-based approaches for spoofing countermeasures
Open source toolkit for speaker verification anti-spoofing