|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
THE DEVELOPMENT OF THE CAMBRIDGE UNIVERSITY RT-04 DIARISATION SYSTEM
S. E. Tranter, M. J. F. Gales, R. Sinha, S. Umesh & P. C. Woodland
This paper describes the development of the Cambridge University RT-04 diarisation system, including details of the new segmentation and clustering components. The final system gives a diarisation error rate of 23.9% on the RT-04 evaluation data, a 34% relative improvement over the RT-03s evaluation system. A further reduction down to 18.1% is shown to be possible when using the segmentation algorithm alone.
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