A structured network architecture for adaptive language acquisition

  • Authors:
  • Laura G. Miller;Allen L. Gorin

  • Affiliations:
  • AT&T Bell Laboratories, Murray Hill, New Jersey;AT&T Bell Laboratories, Murray Hill, New Jersey

  • Venue:
  • ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
  • Year:
  • 1992

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper we report on progress in understanding how to build devices which adaptively acquire the language for their task. The generic device is an information-theoretic connectionist network embedded in a feedback control system. We investigate the capability of the network to learn associations between messages and meaningful responses to them as a task increases in size and complexity. Specifically, we consider how one might reflect task structure in the network architecture in order to provide improved generalization capability in language acquisition. We propose a product network, which provides improved generalization by factoring the associations between words and action through semantic primitives. The product network is being evaluated in several experimental systems, including a 1000-action Almanac data retrieval system. We describe these systems and provide details on two preliminary experiments.