Audio Waveform

Audio waveforms, the fundamental representation of sound as a time-varying pressure wave, are central to numerous audio processing tasks. Current research focuses on improving waveform manipulation and analysis using deep learning architectures like autoencoders, GANs, and diffusion models, often applied to tasks such as audio generation, source separation, and spoofing detection. These advancements are driving progress in applications ranging from enhancing speech quality in telecommunications to creating more realistic and efficient audio synthesis for virtual and augmented reality. The development of efficient and accurate waveform evaluation methods is also a key area of ongoing investigation.