Multi Channel Multi Party Meeting

Multi-channel, multi-party meeting transcription focuses on accurately identifying who spoke what and when in complex audio recordings of meetings involving multiple speakers and microphones. Current research emphasizes improving speaker diarization (identifying who is speaking when) and speaker-attributed automatic speech recognition (ASR) (transcribing speech and assigning it to the correct speaker), often employing techniques like beamforming, attention mechanisms within neural networks (e.g., Conformers), and sophisticated fusion strategies to combine information from multiple channels and models. Advances in this area are crucial for improving meeting summarization, analysis, and accessibility, with significant implications for fields like human-computer interaction and data analytics.