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Voice-controlled modular fuzzy neural controller with enhanced user autonomy

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Abstract

In this article, a fuzzy neural network (FNN)-based approach is presented to interpret imprecise natural language (NL) commands for controlling a machine. This system, (1) interprets fuzzy linguistic information in NL commands for machines, (2) introduces a methodology to implement the contextual meaning of NL commands, and (3) recognizes machine-sensitive words from the running utterances which consist of both in-vocabulary and out-of-vocabulary words. The system achieves these capabilities through a FNN, which is used to interpret fuzzy linguistic information, a hidden Markov model-based key-word spotting system, which is used to identify machine-sensitive words among unrestricted user utterances, and a possible framework to insert the contextual meaning of words into the knowledge base employed in the fuzzy reasoning process. The system is a complete system integration which converts imprecise NL command inputs into their corresponding output signals in order to control a machine. The performance of the system specifications is examined by navigating a mobile robot in real time by unconditional speech utterances.

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Authors and Affiliations

  1. Faculty of Engineering Systems and Technology, Graduate School of Science and Engineering, Saga University, 1-Honjomachi, 840-8502, Saga, Japan

    K. Pulasinghe

  2. Department of Advanced Systems Control Engineering, Saga University, Saga, Japan

    K. Watanabe, K. Kiguchi & K. Izumi

Authors
  1. K. Pulasinghe
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  2. K. Watanabe
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  3. K. Kiguchi
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  4. K. Izumi
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Corresponding author

Correspondence to K. Pulasinghe.

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Pulasinghe, K., Watanabe, K., Kiguchi, K. et al. Voice-controlled modular fuzzy neural controller with enhanced user autonomy. Artif Life Robotics 7, 40–47 (2003). https://doi.org/10.1007/BF02480884

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  • DOI: https://doi.org/10.1007/BF02480884

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