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作 者:郭敬东 吴飞 何德明 卢伟龙 潘建宏 GUO Jingdong;WU Fei;HE Deming;LU Weilong;PAN Jianhong(State Grid Fujian Electric Power Co.,Ltd.,Fuzhou 350000,China;Fujian Yirong Information Technology Co.,Ltd.,Fuzhou 350003,China;State Grid Corporation of China,Beijing 100000,China)
机构地区:[1]国网福建省电力有限公司,福建福州350000 [2]福建亿榕信息技术有限公司,福建福州350003 [3]国家电网有限公司,北京100000
出 处:《微型电脑应用》2024年第9期65-68,76,共5页Microcomputer Applications
基 金:2021年综合网管系统技术支持服务合同(YR-DLL-FJ-RJSS-211116-02478)。
摘 要:为了提升智能问答机器人的语音交互性能,提出一种基于语音识别的智能问答机器人语音交互控制方法。利用用户对智能问答机器人下达语音命令信号的Teager能量,提取语音命令信号的语音特征,基于提取的语音命令信号语音特征,采用隐马尔科夫模型构建智能问答机器人的声学模型,利用该声学模型识别智能问答机器人接收的语音命令。将语音命令识别结果作为最小二乘支持向量机的输入,将智能问答机器人的应答结果作为最小二乘支持向量机的输出,完成智能问答机器人的语音交互控制。实验结果表明,该方法识别语音命令的音素错误率、词错误率低于0.7%,能够获取良好的智能问答机器人语音交互结果。In order to improve the speech interaction performance of intelligent question answering robot,a speech interaction control method based on speech recognition is proposed.The Teager energy of the speech command signal issued by the user to the intelligent question answering robot is used to extract the speech feature of the speech command signal.Based on the speech feature of the extracted speech command signal,the acoustic model of the intelligent question answering robot is constructed using the hidden Markov model,and the speech command received by the intelligent question answering robot is recognized using the acoustic model.The speech command recognition result is taken as the input of the least square support vector machine,and the response result of the intelligent question answering robot is taken as the output of the least square support vector machine to complete the speech interaction control of the intelligent question answering robot.The experimental results show that the phoneme error rate and word error rate of speech commands recognized by this method are lower than 0.7%,and good results of intelligent question answering robot speech interaction can be obtained.
关 键 词:语音识别 智能问答机器人 语音交互 控制方法 隐马尔科夫模型
分 类 号:TP183[自动化与计算机技术—控制理论与控制工程]
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