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作 者:金豪圣 JIN Haosheng(State Grid Zhejiang Electric Power Corporation,Information&Telecommunication Branch,Hangzhou 310000,China)
机构地区:[1]国网浙江省电力有限公司信息通信分公司,浙江杭州310000
出 处:《电子设计工程》2023年第24期95-99,共5页Electronic Design Engineering
摘 要:针对智能机器人语音校准结果不精准的问题,研究基于深度学习的智能机器人语音自动校准系统。设计语音自动校准引擎A/D电路,通过模拟信号发射范围采集与控制电路原始音频信息,利用紧凑型嵌入式音频接收器接收音频信息。整理与识别音频信息内容,获取语句文本样本集。使用深度学习的正弦和余弦函数编码处理方式构建校正模型的输入部分,通过深度学习的前馈神经网络训练输入样本,完成校正模型输出部分的构建。将训练后的样本输入到校正模型中,得到校正后的文本,实现智能机器人语音自动校准。由实验结果可知,该系统两种指令下的振幅波动范围分别为9~22 dB和7~21 dB,与实际振幅波动情况一致,具有精准校准结果。Aiming at the problem of inaccurate voice calibration results of intelligent robot,an automatic voice calibration system of intelligent robot based on deep learning is studied.Design the A/D circuit of voice automatic calibration engine,collect and control the original audio information through the transmission range of analog signal,and receive the audio information by using a compact embedded audio receiver.Sort out and identify the audio information content,and obtain the statement text sample set.The input part of the correction model is constructed by using the sine and cosine function coding processing method of deep learning.The input samples are trained by the feedforward neural network of deep learning to complete the construction of the output part of the correction model.Input the trained samples into the correction model to get the corrected text,and realize the automatic voice calibration of intelligent robot.The experimental results show that the amplitude fluctuation range of the system under the two commands is 9~22 dB and 7~21 dB respectively,which is consistent with the actual amplitude fluctuation and has accurate calibration results.
分 类 号:TN919-34[电子电信—通信与信息系统]
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