基于粗神经网络的仿人智能机器人的语音融合算法研究  

Speech fusion based on rough neural network for humanoid intelligent robots

作　　者：刘国良[1] 强文义[1] 麻亮[1] 陈兴林[1] 

机构地区：[1]哈尔滨工业大学控制科学与工程系,黑龙江哈尔滨150001

出　　处：《控制与决策》2003年第3期364-366,共3页Control and Decision

基　　金：哈尔滨工业大学校基金资助项目 ( HIT.2 0 0 1.0 3 )

摘　　要：将粗集合理论与神经网络相结合 ,提出一种基于粗神经网络的新的信息融合方法 ,用于仿人智能机器人的语音融合。该方法不仅可以接受定量输入 ,而且可以接受定性输入 ,即输入是一个范围 ,或在观测时间内输入是变化的。由于粗神经网络的误差传递函数不可微 ,所以采用遗传算法来训练粗神经网络。仿真实验结果表明 。Integrating rough set theory with neural network theory, a novel information fusion method based on rough neural network is proposed. It is used in speech fusion of humanoid intelligent robots. The input could be qualitative, i.e. a range or variational during the observation, as well as quantitative. Because the error transfer function of rough neural network is not differentiable, genetic algorithms are applied for training the network. The simulation results indicated that the novel information fusion method based on rough neural network does improve the speech recognition probability.

关 键 词：粗神经网络 信息融合 语音识别 仿人智能机器人 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]