Diarization Result

Speaker diarization, the task of identifying who spoke when in an audio recording, aims to automatically segment audio streams by speaker. Current research focuses on improving the speed and accuracy of diarization systems, exploring techniques like knowledge distillation, quantization, and graph neural networks to optimize model architectures such as encoder-decoder models and Gaussian Mixture Models (GMMs). These advancements are crucial for applications ranging from meeting transcription to improving the efficiency of other speech processing tasks like automatic speech recognition, impacting both research methodologies and real-world applications.