Audio Data

Audio data analysis is a rapidly evolving field focused on extracting meaningful information from sound recordings, encompassing diverse applications from speech recognition and music information retrieval to environmental monitoring and healthcare. Current research emphasizes developing robust models, often based on deep neural networks like convolutional neural networks (CNNs) and transformers, for tasks such as anomaly detection, sound event localization, and classification, frequently incorporating self-supervised and semi-supervised learning techniques to address data scarcity issues. These advancements are driving progress in various sectors, including improved accessibility for individuals with disabilities, enhanced healthcare diagnostics, and more efficient data management for large-scale audio archives.