Title: Fast word acquisition in an NMF-based learning framework
Authors: Driesen, Joris
Van hamme, Hugo
Issue Date: 2012
Host Document: Proceedings ICASSP’2012 pages:5137-5140
Conference: International conference on acoustics, speech and signal processing - ICASSP’2012 edition:37 location:Kyoto, Japan date:25-30 March 2012
Abstract: A speech recognition system that automatically learns word models for a small vocabulary from examples of its usage, without using prior linguistic information, can be of great use in cognitive robotics, human-machine interfaces, and assistive devices. In the latter case, the user's speech
capabilities may also be affected. In this paper, we consider a NMF-based learning framework capable of doing this, and experimentally show that its learning rate crucially depends on how the speech data is represented.
Higher-level units of speech, which hide some of the complex variability of the acoustics, are found to yield faster learning rates.
Description: Driesen J., Van hamme H., ''Fast word acquisition in an NMF-based learning framework'', Proceedings 37th international conference on acoustics, speech and signal processing - ICASSP’2012, pp. 5137-5140, March 25-30, 2012, Kyoto, Japan.
ISBN: 978-1-4673-0046-9
Publication status: published
KU Leuven publication type: IC
Appears in Collections:ESAT - PSI, Processing Speech and Images

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