Recursive distributed representations
Artificial Intelligence - On connectionist symbol processing
Learning and applying contextual constraints in sentence comprehension
Artificial Intelligence - On connectionist symbol processing
Distributed Representations, Simple Recurrent Networks, And Grammatical Structure
Machine Learning - Connectionist approaches to language learning
Induction of finite-state languages using second-order recurrent networks
Neural Computation
How to design a connectionist holistic parser
Neural Computation
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
Natural Language Grammatical Inference with Recurrent Neural Networks
IEEE Transactions on Knowledge and Data Engineering
Dialogue act modeling for automatic tagging and recognition of conversational speech
Computational Linguistics
Learning distributed representations for the classification of terms
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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This paper shows an application of four neural networks architectures for the automatic adaptation of the voice interface to a robotic system. These architectures are flexible enough to allow a nonspecialist user to train the interface to recognize the syntax of new commands to the teleoperated environment. The system has been tested in a real experimental robotic system applied to perform simple assembly tasks, and the experiments have shown that the networks are robust and efficient for the trained tasks.