Speaker Diarization

Speaker diarization is the task of identifying "who spoke when" in an audio recording, a crucial preprocessing step for many speech applications. Current research focuses on improving accuracy and efficiency, particularly in challenging scenarios like multi-speaker conversations and noisy environments, using techniques such as end-to-end neural networks, spectral clustering, and the integration of audio-visual or semantic information. These advancements are driving progress in areas like meeting transcription, multilingual speech processing, and improving the performance of downstream tasks such as automatic speech recognition.