Abstract
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.
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Ñeco, R.P., Reinoso, Ó., Azorín, J.M., Sabater, J.M., Asunción Vicente, M., García, N. (2002). Automatic Adaptation of a Natural Language Interface to a Robotic System. In: Garijo, F.J., Riquelme, J.C., Toro, M. (eds) Advances in Artificial Intelligence — IBERAMIA 2002. IBERAMIA 2002. Lecture Notes in Computer Science(), vol 2527. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36131-6_73
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DOI: https://doi.org/10.1007/3-540-36131-6_73
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