Raw Audio

Raw audio analysis is a rapidly evolving field focused on extracting meaningful information directly from unprocessed sound waveforms, bypassing traditional feature extraction methods. Current research emphasizes the development of deep learning models, particularly transformer and convolutional neural networks (CNNs), often incorporating techniques like self-supervised learning and curriculum optimization to handle challenges such as data scarcity and high polyphony. These advancements are improving applications across diverse domains, including bioacoustic monitoring, music generation evaluation, speech emotion recognition, and audio tampering detection, ultimately leading to more accurate and efficient analysis of complex audio data.