AI-Enhanced Beamforming: Advancements and Challenges in Spatial Audio and Voice Processing

Beamforming is a fundamental technology to provide quality voice and speech in voice and audio processing. It also plays a critical role in applications like smart speakers, conferencing systems, and voice-controlled IoT devices. Traditional beamforming techniques, including delay-and-sum and MVDR (Minimum Variance Distortion Less Response), have been widely used but face challenges in dynamic and reverberant environments. AI-driven beamforming has opened new avenues for adaptive and intelligent spatial filtering. This paper discusses the latest advancements in AI-based beamforming, discusses key challenges such as computational efficiency and real-world robustness, and outlines future directions for integrating deep learning into beamforming pipelines. In conclusion, we will demonstrate how AI-based beamforming techniques outperform traditional accuracy, adaptability, and efficiency methods.