Audio Processing

Audio processing research focuses on efficiently and accurately analyzing, manipulating, and generating audio signals for diverse applications. Current efforts concentrate on developing robust models for tasks like speech enhancement, music transcription, and sound event detection, often employing deep learning architectures such as transformers, convolutional neural networks, and diffusion models, alongside techniques like meta-learning and continual learning to improve efficiency and adaptability. These advancements are driving progress in areas ranging from hearing aid technology and personalized music therapy to improved security systems and more realistic audio generation, impacting both scientific understanding and real-world applications.