Fig. 2: Overview of a generic deep learning-based SELD pipeline.
From: Environmental acoustic intelligence through sound event localization and detection: a review
Multi-channel audio is recorded with detailed annotations of event types and spatial origins. After converting the raw signals into time-frequency and spatial features, potentially with data augmentation to improve model generalization, a neural network infers both event labels and DOA coordinates on a frame-by-frame basis. Final predictions are benchmarked using standardized metrics, informing iterative improvements for real-world readiness.
