Speaker Diarization

The process of partitioning an audio stream into segments according to speaker identity, determining "who spoke when" in a multi-speaker recording or conversation. Speaker diarization is important for accessibility because deaf and hard of hearing individuals need to distinguish between different speakers in social settings, meetings, and group conversations. It is also critical for accurate captioning and transcription systems. Modern diarization approaches use neural network-based speaker embeddings and can handle overlapping speech, though real-time performance in noisy environments remains challenging.