Audio Recognition

Audio recognition research focuses on developing computational systems that can accurately identify and classify sounds, with applications ranging from ecological monitoring to assistive technologies for the hearing impaired. Current efforts center on improving model architectures, such as Transformers and MLP-Mixers, and exploring efficient feature extraction methods using spectrograms and scalograms, often incorporating attention mechanisms for enhanced temporal processing. These advancements aim to create more robust, efficient, and adaptable systems, particularly for resource-constrained environments and personalized applications, ultimately impacting fields like environmental monitoring, human-computer interaction, and healthcare.