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Related Experiment Videos

Modular fuzzy-neuro controller driven by spoken language commands.

Koliya Pulasinghe1, Keigo Watanabe, Kiyotaka Izumi

  • 1Department of Advanced Systems Control Engineering, Saga University, Saga 840-8502, Japan.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|September 17, 2004
PubMed
Summary

This study introduces a novel speech interface for machine control, addressing fuzzy word meanings and out-of-vocabulary challenges. The system successfully navigated a mobile robot using spoken language commands.

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Speech interfaces for machine control face challenges with ambiguous language and unrecognized words.
  • Existing systems struggle to interpret nuanced commands and handle conversational speech effectively.

Purpose of the Study:

  • To develop a robust methodology for controlling machines via spoken language commands.
  • To address the interpretation of fuzzy implications and out-of-vocabulary words in natural speech.
  • To enhance machine responsiveness to user intent through contextual word significance.

Main Methods:

  • Utilized a hidden Markov model (HMM) based automatic speech recognizer (ASR) for speech input.
  • Implemented a keyword spotting system to identify critical machine-related terms.

Related Experiment Videos

  • Employed a fuzzy-neural network (FNN) controller to manage linguistic ambiguity and fuzzy word meanings.
  • Integrated contextual word significance based on the machine's state.

    • Main Results:

    • The system demonstrated effective real-time navigation of a mobile robot using spoken commands.
    • Successfully interpreted words with fuzzy implications and handled out-of-vocabulary words.
    • Achieved more realistic and user-aligned machine outputs through contextual understanding.

    Conclusions:

    • The proposed methodology offers a significant advancement in spoken language control for machines.
    • The modular system design allows for generalization across various machine functions.
    • This approach enhances human-robot interaction by enabling more natural and intuitive communication.