Implementation Voice Command System for Soccer Robot ERSOW

Muhammad Rizal Prasetyo, Iwan Kumianto Wibowo, M. Bachtiar, Renardi Adryantoro Priambudi, Khoirul Anwar, Putu Bagus Kertha Segara
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Abstract

ERSOW is a wheeled soccer robot that is included in the Middle Size League (MSL) category in the Indonesian Wheeled Robot Soccer Contest division (Wheeled KRSBI). Wheeled soccer robot has Artificial Intelligent (AI) for kick the ball, receive the ball, feed the ball, recognize the ball, recognize the opponent, recognize the goal, receive instructions from the base station, and so forth. This research focuses on giving instructions to ERSOW through the base station using the voice command system. The system uses speech as input in the form of analog signals. Speech recognition is done by using a deep speech package so as to produce output in the form of text. The system will run on the Robot Operating System (ROS). The result of speech recognition using 13 trained speakers when tested by one speaker in different distance show average Word Error Rate (WER) 0.46% and Word Accuracy (W Acc) is 99.54%. When tested by five different speaker using trained speakers show average WER is 4.37% and W Acc is 95.63%, when using non trained speakers show average WER is 28.25% and W Acc is 71.75%. Base station implementation shows the simulation of the robot when the user gives instruction by his or her own voice.
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足球机器人ERSOW语音指挥系统的实现
ERSOW是一款轮式足球机器人,被列入印度尼西亚轮式机器人足球大赛(轮式KRSBI)的中型联赛(MSL)类别。轮式足球机器人具有人工智能(AI),用于踢球、接球、喂球、识别球、识别对手、识别进球、接收来自基站的指令等。本研究的重点是利用语音指挥系统,通过基站对ERSOW进行指令。该系统使用语音作为模拟信号的输入。语音识别是通过使用深度语音包来产生文本形式的输出。该系统将在机器人操作系统(ROS)上运行。对13个经过训练的说话人进行语音识别,当一个说话人在不同距离上进行测试时,平均单词错误率(WER)为0.46%,单词正确率(wacc)为99.54%。当使用经过训练的说话者对5个不同的说话者进行测试时,平均WER为4.37%,W Acc为95.63%,当使用未经训练的说话者时,平均WER为28.25%,W Acc为71.75%。基站实现显示了当用户通过自己的声音发出指令时机器人的仿真。
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