Method of speaker clustering for unknown speakers in conversational

Abstract

A method for clustering speaker data from a plurality of unknown speakers. The method includes steps of providing a portion of audio data containing speech from at least all the speakers in the audio data and dividing the portion into data clusters. A pairwise distance between each pair of clusters is computed, the pairwise distance being based on a likelihood that two clusters were created by the same speaker, the likelihood measurement being biased by the prior probability of speaker changes. The two clusters with a minimum pairwise distance are combined into a new cluster and speakers models are trained for each of the remaining clusters including the new cluster. The likelihood that two clusters were created by the same speaker may be biased by a Markov duration model based on speaker changes over the length of the initial data clusters.