Cerebellum-like neural network for short-range timing function of a robotic speaking system

Thanh Vo Nhu, Hideyuki Sawada

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    The timing control is necessary for determining its duration, stress, and rhythm in human speech; however, little attention has been paid to these issues when building a speech synthesis system. We have developed a talking robot, which generates human-like vocal sounds. The cerebellum is an important part of human brain organ that has a significant role in the coordination, precision, and timing of motor responses. In this study, we develop a simplified cerebellumlike spiking neural network model to control the timing function for the talking robot. The model was designed using the System Generator software in Matlab, and the timing duration of trained speech was estimated using hardware cosimulated with a field programmable gate array board (FPGA). The timing information obtained from the co-simulation, together with the output motor vector, is sent to the talking robot controller to generate a sound with a short duration. The result indicates that this model can be used for short-range timing learning of the talking robot.

    Original languageEnglish
    Title of host publication2017 3rd International Conference on Control, Automation and Robotics, ICCAR 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages184-187
    Number of pages4
    ISBN (Electronic)9781509060870
    DOIs
    Publication statusPublished - 2017 Jun 7
    Event3rd International Conference on Control, Automation and Robotics, ICCAR 2017 - Nagoya, Japan
    Duration: 2017 Apr 222017 Apr 24

    Other

    Other3rd International Conference on Control, Automation and Robotics, ICCAR 2017
    CountryJapan
    CityNagoya
    Period17/4/2217/4/24

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    Keywords

    • Cerebellum-like neural network
    • FPGA
    • Talking-robot
    • Timing control

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Control and Optimization
    • Control and Systems Engineering

    Cite this

    Nhu, T. V., & Sawada, H. (2017). Cerebellum-like neural network for short-range timing function of a robotic speaking system. In 2017 3rd International Conference on Control, Automation and Robotics, ICCAR 2017 (pp. 184-187). [7942683] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCAR.2017.7942683