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Speaker Recognition on Single- and Multispeaker Data

✍ Scribed by Frederick Weber; Barbara Peskin; Michael Newman; Andrés Corrada-Emmanuel; Larry Gillick

Publisher
Elsevier Science
Year
2000
Tongue
English
Weight
240 KB
Volume
10
Category
Article
ISSN
1051-2004

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✦ Synopsis

We discuss Dragon Systems' approach to the NIST Speaker Recognition tasks. For the one-speaker task, we employ a combination of methods: a basic GMM system and two LVCSR-based systems, one using standard mixture models and the other using nonparametric techniques. We discuss some explorations of the recently introduced two-speaker tasks based on the GMM system alone. "Cheating" tests using NIST-supplied keys lead us to some improvements in channel normalization, and illuminate the roles that speaker segmentation and segment selection play in these tasks.

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