Audio Manipulation

Audio manipulation encompasses the creation and detection of altered or artificially generated audio, driven by advancements in generative models and the need to ensure audio authenticity. Current research focuses on developing robust detection methods, often employing machine learning classifiers and transformer networks, alongside techniques for manipulating audio signals using novel approaches like differentiable wavetable synthesis and acoustic metascreens for precise control of reflection and transmission. These advancements have significant implications for combating audio deepfakes, improving accessibility in mixed-reality environments, and enhancing forensic audio analysis.