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

Thanh Vo Nhu, Hideyuki Sawada

    研究成果: Conference contribution

    2 被引用数 (Scopus)

    抄録

    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.

    本文言語English
    ホスト出版物のタイトル2017 3rd International Conference on Control, Automation and Robotics, ICCAR 2017
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ184-187
    ページ数4
    ISBN(電子版)9781509060870
    DOI
    出版ステータスPublished - 2017 6 7
    イベント3rd International Conference on Control, Automation and Robotics, ICCAR 2017 - Nagoya, Japan
    継続期間: 2017 4 222017 4 24

    Other

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

    ASJC Scopus subject areas

    • 人工知能
    • 制御と最適化
    • 制御およびシステム工学

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