Centre for High Performance Computing 2021 National Conference

Unsupervised fine-tuning of speaker diarisation pipelines using silhouette coefficients.

Not scheduled

20m

Student Micro-talk Cognitive Computing and Machine Learning Micro-talks

Speaker

Mr Lucas van Wyk (North West University)

Description

We investigate the use of silhouette coefficients in cluster analysis for speaker diarisation, with the dual purpose of unsupervised fine-tuning during domain adaptation and determining the number of speakers in an audio file. Our main contribution is to demonstrate the use of silhouette coefficients to perform per-file domain adaptation, which we show to deliver an improvement over per-corpus domain adaptation. Secondly, we show that this method of silhouette-based cluster analysis can be used to accurately determine more than one hyperparameter at the same time. Finally, we propose a novel method for calculating the silhouette coefficient of clusters using a PLDA score matrix as input.