Speaker verification using text-constrained Gaussian mixture models
May 13, 2002
Conference Paper
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Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, Vol. I, 13-17 May 2002, pp. I-677 - I-680.
R&D Area:
Summary
In this paper we present an approach to close the gap between text-dependent and text-independent speaker verification performance. Text-constrained GMM-UBM systems are created using word segmentations produced by a LVCSR system on conversational speech allowing the system to focus on speaker differences over a constrained set of acoustic units. Results on the 2001 NiST extended data task show this approach can be used to produce an equal error rate of < 1%.