This repository organizes the world’s resources for speaker diarization, a speech processing task that identifies who spoke when in audio recordings. The curated list covers publications including review and survey papers on deep learning approaches, software frameworks for clustering and speaker embedding, evaluation tools, datasets for training and augmentation, and other learning materials such as courses, books, and tutorials. It serves as a centralized reference for practitioners and researchers in the speech and audio processing community.