Review of neural networks for speech recognition
Neural Computation
The cascade-correlation learning architecture
Advances in neural information processing systems 2
A resource-allocating network for function interpolation
Neural Computation
On-line learning in neural networks
On-line learning in neural networks
Evolving Connectionist Systems: Methods and Applications in Bioinformatics, Brain Study and Intelligent Machines
Evolving fuzzy neural networks for supervised/unsupervised onlineknowledge-based learning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Evolutionary learning of nearest-neighbor MLP
IEEE Transactions on Neural Networks
Thai spelling analysis for automatic spelling speech recognition
Information Sciences: an International Journal
| Hi-index | 0.00 |
The paper presents a novel approach towards building adaptive speech recognition systems based on the evolving connectionist systems paradigm (ECoS). The simple evolving connectionist systems are the minimalist implementation of the ECoS. They can accommodate new input data and new classes through local element tuning. New connections and neurons are created during the adaptive learning process of the system. Experiments are conducted to illustrate this concept. It is demonstrated that a system can adapt to new speakers data and add new output classes on-line, e.g. new words, added at any time of its operation without having to rebuild the network from "scratch". The system is robust to forgetting when new words are added.