Audio Understanding

Audio understanding research aims to enable computers to process and interpret audio information, mirroring human auditory capabilities. Current efforts focus on developing robust audio-language models (ALMs) using transformer architectures and other deep learning techniques, often incorporating multimodal approaches that integrate visual or textual data to enhance understanding. These advancements are driving progress in various applications, including music information retrieval, sound event detection, and assistive technologies for individuals with hearing impairments, while also providing insights into human cognitive processes related to sound perception and language. The development of large-scale datasets and standardized benchmarks is crucial for evaluating and comparing these models, fostering further progress in the field.