Sound source localization technology has been developing rapidly in the military and civil fields; however, it still has certain limitations in large-scale manufactory or industrial site with the noise and complex sound field environments. So, the single sound source localization algorithm based on the microphone array model of the multilayer perceptron was studied, firstly, a three-point microphone array model was built to collect and process the sound wave signals, then the Time-Differences-of-Arrival (TDOA) and sound pressure level of microphone signals were extracted to as feature vectors, and multilayer perceptron sound source localization algorithm with multiple features and multiple hidden layers was constructed. Based on the python machine learning toolbox-sklearn, the algorithm was implemented and simulated, and the result shows that it has better performance and robustness compared with other machine learning sound source localization algorithms.


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    Title :

    Research on Sound Source Localization Algorithm Based on Multilayer Perceptron


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Wang, Yi (editor) / Martinsen, Kristian (editor) / Yu, Tao (editor) / Wang, Kesheng (editor) / Zhang, Jinliang (author) / Weng, Xianfeng (author) / Zhou, Jing (author) / Li, DongPing (author)

    Conference:

    International Workshop of Advanced Manufacturing and Automation ; 2020 ; Zhanjiang, China October 12, 2020 - October 13, 2020



    Publication date :

    2021-01-23


    Size :

    7 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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