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Speech recognition and control system for the severely disabled.

A Cohen, D Graupe

    Journal of Biomedical Engineering
    |April 1, 1980
    PubMed
    Summary
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    This study presents a microprocessor-based speech recognition system for assistive technology. The system achieves high accuracy for voice control applications, demonstrating its viability for the disabled.

    Area of Science:

    • Computer Science
    • Engineering
    • Assistive Technology

    Background:

    • Microprocessors enable cost-effective speech recognition for constrained applications like assistive devices.
    • Existing systems face challenges with microprocessor limitations such as finite word length and slower processing speeds.

    Purpose of the Study:

    • To describe a microprocessor-based speech recognition system for voice control of assistive devices.
    • To present algorithms for feature extraction, classification, and training suitable for microprocessors.
    • To evaluate the system's performance on a ten-digit recognition task.

    Main Methods:

    • Utilized autoregressive (linear prediction coefficients) for feature extraction.
    • Developed classification and training algorithms optimized for microprocessor constraints.

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  • Implemented a hierarchical memory organization for efficient processing.

    • Main Results:

    • The system demonstrated high accuracy in recognizing a ten-digit set for touch-tone phone activation.
    • Achieved less than one percent substitution errors.
    • Reported eleven percent rejection errors, indicating robustness.

    Conclusions:

    • Microprocessor-based speech recognition is feasible for assistive technology despite computational constraints.
    • The developed algorithms and system architecture are effective for voice control applications.
    • The system shows potential for enhancing independence for individuals with severe disabilities.