Meeting Scenario

Research on meeting scenarios focuses on automatically understanding and processing the audio and video data generated during virtual and in-person meetings. Current efforts concentrate on improving speaker diarization, speech recognition, and active speaker detection, often employing neural networks and advanced signal processing techniques to handle challenges like overlapping speech, varying audio quality, and dynamic participant layouts. These advancements are crucial for creating efficient tools for meeting transcription, summarization, and analysis, impacting fields ranging from collaborative work to educational technology. The development of large, high-quality datasets is also a key focus to enable the training and evaluation of robust algorithms.