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.
Papers
December 4, 2024
October 9, 2024
July 19, 2024
July 1, 2024
June 3, 2024
March 31, 2024
February 19, 2024
February 2, 2024
December 26, 2023
September 11, 2023
August 25, 2023
May 23, 2023
October 27, 2022
October 19, 2022
June 16, 2022
February 17, 2022