Sciweavers

Share
INTERSPEECH
2010

Incremental word learning using large-margin discriminative training and variance floor estimation

8 years 7 months ago
Incremental word learning using large-margin discriminative training and variance floor estimation
We investigate incremental word learning in a Hidden Markov Model (HMM) framework suitable for human-robot interaction. In interactive learning, the tutoring time is a crucial factor. Hence our goal is to use as few training samples as possible while maintaining a good performance level. To adapt the states of the HMMs, different large-margin discriminative training strategies for increasing the separability of the classes are proposed. We also present a novel estimation of the variance floor when a very low number of training data is used. Finally our approach is successfully evaluated on isolated digits taken from the TIDIGITS database.
Irene Ayllón Clemente, Martin Heckmann, Ale
Added 18 May 2011
Updated 18 May 2011
Type Journal
Year 2010
Where INTERSPEECH
Authors Irene Ayllón Clemente, Martin Heckmann, Alexander Denecke, Britta Wrede, Christian Goerick
Comments (0)
books