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» Parallel Training of Neural Networks for Speech Recognition
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IJISTA
2007
124views more  IJISTA 2007»
14 years 9 months ago
Incremental learning for spoken affect classification and its application in call-centres
: This paper introduces a system for real-time incremental learning in a call-centre environment. The classifier used is a Support Vector Machine (SVM) and it is applied to telepho...
Donn Morrison, Ruili Wang, W. L. Xu, Liyanage C. D...
IJCNN
2008
IEEE
15 years 4 months ago
A comparison of fuzzy ARTMAP and Gaussian ARTMAP neural networks for incremental learning
Abstract— Automatic pattern classifiers that allow for incremental learning can adapt internal class models efficiently in response to new information, without having to retrai...
Eric Granger, Jean-François Connolly, Rober...
72
Voted
LREC
2010
155views Education» more  LREC 2010»
14 years 11 months ago
WTIMIT: The TIMIT Speech Corpus Transmitted Over The 3G AMR Wideband Mobile Network
Due to upcoming mobile telephony services with higher speech quality, a wideband (50 Hz to 7 kHz) mobile telephony derivative of TIMIT has been recorded called WTIMIT. It allows a...
Patrick Bauer, David Scheler, Tim Fingscheidt
64
Voted
ICONIP
2004
14 years 11 months ago
Collaborative Agent Learning Using Neurocomputing
In this paper we investigate techniques to train an agent to accomplish certain tasks. Artificial Neural Networks will be the technique used to the train the agent. This paper will...
Saulat Farooque, Ajith Abraham, Lakhmi C. Jain
63
Voted
IJCNN
2006
IEEE
15 years 3 months ago
Preparing More Effective Liquid State Machines Using Hebbian Learning
—In Liquid State Machines, separation is a critical attribute of the liquid—which is traditionally not trained. The effects of using Hebbian learning in the liquid to improve s...
David Norton, Dan Ventura