Generalized Viterbi-based models for time-series segmentation and clustering applied to speaker diarization

We carry out diarizations of two-speaker telephone conversations in order to evaluate the performance of HDM. When applied to conversations from the LDC CALLHOME database, HDM improves on the performance of a baseline HMM system by about 26% (relative improvement). Moreover, when applied to the NIST 2005 database, it yields a small improvement over the HMM system.