Directivity Pattern

Directivity pattern research focuses on controlling the spatial distribution of acoustic or visual signals, aiming to enhance signal quality and efficiency in various applications. Current research employs diverse approaches, including deep neural networks for microphone array processing, optimization algorithms for loudspeaker beamforming to achieve constant directivity, and machine learning models for reconstructing dynamic directivity patterns from limited data. These advancements have significant implications for fields like audio engineering (e.g., improved speech capture and sound reproduction), robotics (e.g., enhanced visual perception in search and rescue), and communication technologies (e.g., more realistic virtual communication).