Echo Cancellation

Acoustic echo cancellation (AEC) aims to remove unwanted echoes from audio signals, improving the quality of communication and speech recognition systems. Current research emphasizes developing computationally efficient AEC models, often employing deep neural networks (DNNs) such as conformers, recurrent UNets, and diffusion models, sometimes integrated with Kalman filters or adaptive filters, to achieve real-time performance on resource-constrained devices. These advancements focus on joint processing of echo cancellation with noise reduction and speech enhancement, often incorporating personalized approaches using speaker embeddings to improve performance and reduce distortion. The resulting improvements in speech quality and intelligibility have significant implications for various applications, including teleconferencing, hands-free devices, and assistive listening technologies.