Yangxia Hu

Papers

Total Citations

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About

Yangxia Hu is a researcher whose work bridges the fields of audio security and machine learning, with a particular focus on developing robust watermarking techniques for voice data. Her most notable contribution, the 2023 paper "A watermark detection scheme based on non-parametric model applied to mute machine voice," introduces an innovative approach that leverages non-parametric statistical models to embed and detect watermarks in silent segments of machine-generated speech. This work addresses a critical gap in audio forensics, where traditional watermarking methods often fail in low-signal environments. With 4 citations since its publication, the study has already garnered attention from peers exploring intellectual property protection for synthetic voice technologies—a rapidly growing concern with the rise of deepfake audio. Hu's research is particularly relevant for applications in voice assistant security, digital rights management, and anti-spoofing systems. By tackling the challenge of watermarking in mute or near-silent audio frames, she provides a foundation for more resilient and imperceptible audio authentication methods. Her work exemplifies how non-parametric models can offer flexible, data-driven solutions to real-world security problems in voice-based systems.