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Speech Recognition based on BP Network with Improved Learning Algorithm in Application on Industrial Robots

机译:基于BP网络的语音识别,改进了工业机器人应用中的应用中的学习算法

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A three layer feed-forward neural network is developed for speech recognition for industrial robots. The signal is made up by four kinds of command sound. Based on the steepest descent method, the BP network is trained by an improved learning algorithm in which momentum factor and learning rate adjustment is adopted. The simulation results indicates that the error in classification small also with high recognition correct in terms of a percentage.
机译:为工业机器人的语音识别开发了三层前馈神经网络。 该信号由四种命令声音组成。 基于陡峭的下降方法,通过改进的学习算法训练BP网络,其中采用动量因子和学习速率调整。 仿真结果表明,在百分比方面,分类中的分类误差也很高。

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