Studying Human-Based Speaker Diarization and Comparing to State-of-the-Art Systems
Published in ASPIPA, 2022
Recommended citation: S. W. McKnight, A. O. T. Hogg, V. W. Neo, and P. A. Naylor, "Studying human-based speaker diarization and comparing to state-of-the-art systems," in Proc. Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Nov. 2022.
This paper compares the performance of human-based speaker diarization against state-of-the-art machine learning systems.
Resources will be made available later.
Recommended citation: ‘S. W. McKnight, A. O. T. Hogg, V. W. Neo, and P. A. Naylor, “Studying human-based speaker diarization and comparing to state-of-the-art systems,” in Proc. Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Nov. 2022.’