Related Research: Advances in Lightweight Audio Forgery Detection

For those interested in the wider context of detecting synthetic and manipulated audio, two recent papers offer valuable insights and inspiration for the Blueprint:

• Improved DeepFake Detection Using Whisper Features: This paper explores how features extracted from OpenAI’s Whisper model can improve detection accuracy when combined with classical architectures like LCNN and MesoNet.‍
• MLAAD: The Multi-Language Audio Anti-Spoofing Dataset: Introduces a large multilingual dataset for synthetic speech detection, designed to improve cross-language generalization. It shows the importance of diverse training data in building robust detection systems

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