Robust Speaker Diarization for Short Speech Recordings

We investigate a state-of-the-art Speaker Diarization system regarding its behavior on meetings that are much shorter (from 500 seconds down to 100 seconds) than those typically analyzed in Speaker Diarization benchmarks. First, the problems inherent to this task are analyzed. Then, we propose an approach that consists of a novel initialization parameter estimation method for typical state-of-the-art diarization approaches. The estimation method balances the relationship between the optimal value of the duration of speech data per Gaussian and the duration of the speech data, which is verified experimentally for the first time in this article. As a result, the Diarization Error Rate for short meetings extracted from the 2006, 2007, and 2009 NIST RT evaluation data is decreased by up to 50% relative.


Presented at:
Proceedings of the IEEE workshop on Automatic Speech Recognition and Understanding, Merano, Italy
Year:
2009
Laboratories:




 Record created 2010-02-11, last modified 2018-03-17

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