Overlapped Speech Detection

Overlapped speech detection (OSD) aims to identify when multiple speakers are talking simultaneously, a crucial preprocessing step for applications like speaker diarization and meeting transcription. Current research focuses on improving OSD accuracy and robustness using various techniques, including attention-based channel combination algorithms, large-scale learning with conformer networks, and two-stage frameworks that incorporate overlap-aware post-processing. Advances in OSD are vital for enhancing the performance of speech processing systems in real-world scenarios characterized by multi-party conversations and noisy environments, leading to more accurate and efficient transcription and analysis of audio data.