An unsupervised, sequential learning algorithm for the segmentation of speech waveforms with multiple speakers

The authors present a method for segmenting speech waveforms containing several speakers into utterances, each from one individual, and then identifying each utterance as coming from a specific individual or group of individuals. The procedure is unsupervised in that there is no training set, and sequential in that information obtained in early stages of the process is utilized in later stages.<<ETX>>