|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
THE CAMBRIDGE UNIVERSITY MARCH 2005 SPEAKER DIARISATION SYSTEM
R. Sinha, S. E. Tranter, M.J.F. Gales & P.C. Woodland
This paper describes the speaker diarisation system developed at Cambridge University in March 2005. This system combines techniques used successfully in our previous speaker diarisation systems with an additional second clustering stage based on state-of-the-art speaker identification methods. Several strategies for using the new system are investigated and the final system gives a diarisation error rate of 6.9% on the RT-04 Fall diarisation evaluation data when processing all the test data together or 8.6% when processing the test data shows independently.
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2005 Cambridge University Engineering Dept
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