Speech segmentation and clustering based on speaker features

The authors describe speech segmentation and clustering algorithms based on speaker features, where speakers, the number of speakers, and speech context are unknown. Several problems are formulated and their solutions are proposed. As in the simpler case, when speech segmentations are known, the output probability clustering algorithm is proposed. In the case of unknown segmentation, an ergodic HMM (hidden Markov model)-based technique is applicable. Both cases are evaluated using simulated multispeaker dialogue speech data. >