Neuromorphic Audio

Neuromorphic audio processing aims to replicate aspects of human auditory processing using energy-efficient, brain-inspired spiking neural networks (SNNs). Current research focuses on developing SNN architectures and algorithms, such as those incorporating adaptive locally competitive algorithms and transformer-enhanced models, for tasks like speech enhancement and classification. This field is significant due to its potential for creating ultra-low-power audio applications for edge devices, improving performance in noisy environments, and offering novel approaches to audio security and intellectual property protection.