Modular construction of time-delay neural networks for speech recognition
Neural Computation
Language (vol.1)
Neural Networks
The handbook of brain theory and neural networks
A hard wired model of coupled frontal working memories for various tasks
Information Sciences: an International Journal
How to design a connectionist holistic parser
Neural Computation
Self-Organizing Maps
A Recurrent Self-Organizing Map for Temporal Sequence Processing
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Constructing Symbols as Manipulable Structures by Recurrent Networks
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2 - Volume 2
Artificial Creativity in Linguistics Using Evolvable Fuzzy Neural Networks
ICES '08 Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware
Evolvable Neuro-fuzzy System for Artificial Creativity in Linguistics
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Neurocomputing
Hi-index | 0.00 |
The neural networks that achieve linguistic skills in the brain are presently being uncovered by brain imaging methods using suitable psychophysical paradigms. We use these and other related results to guide the development of an overall neural architecture to implement Chomsky's "Language Acquisition Device" or LAD. We then consider in more detail the twin problems of the generation of infinite length sequences and the complexity of the recurrent system that produces such sequences. A recurrent neural network approach is used, based on our cartoon version of the frontal lobes, to analyze these two problems. The first is shown to be soluble in principle for any set of words by means of a set of "phrase analyzers", which contain complex neurones able to chunk suitable sequences. Further guidance from action and precept representations is indicated as helpful. The second problem is found to be solved by using the simplest level of chunking; this arises naturally in the learning process, according to a set of simulations, provided the task of language learning is suitably hard. We conclude with an overview of future developments to allow a full LAD to be developed so as to begin to approach adult speech.