Acoustic Howling Suppression

Acoustic howling suppression (AHS) aims to eliminate the unwanted feedback loops that create a loud, unpleasant whistling sound in audio systems. Current research heavily focuses on hybrid approaches combining traditional signal processing techniques like Kalman filtering with deep learning models, particularly recurrent neural networks (RNNs) and self-attentive architectures, to achieve robust and real-time suppression. These methods often employ teacher-forced training strategies to overcome the challenges posed by the inherently recursive nature of howling. Improved AHS techniques are crucial for enhancing the quality of audio communication in various applications, including video conferencing and hearing aids.