Unsupervised Speaker Clustering in a Linear Discriminant Subspace


We present an approach for grouping single-speaker speech segments into speaker-specific clusters. Our approach is based on applying the K-means clustering algorithm to a suitable discriminant subspace, where the euclidean distance reflect speaker differences. A core feature of our approach is approximating speaker-conditional statistics, that are not… (More)
DOI: 10.1109/ICMLA.2010.159

2 Figures and Tables


  • Presentations referencing similar topics