Acoustic Beamforming

Acoustic beamforming focuses on enhancing sounds from specific directions while suppressing noise from others, using microphone arrays to achieve directional audio capture. Current research emphasizes data-driven approaches, employing convolutional recurrent neural networks and other deep learning architectures to improve beamforming performance, particularly in challenging acoustic environments and with limited microphone resources. These advancements are impacting various fields, including room geometry inference, object distance estimation for autonomous vehicles, and speech enhancement in noisy settings, by providing more robust and efficient solutions for directional audio processing.