摘要
本文提出了一种基于脉冲神经网络SNN的语音识别方法。该方法以H-H脉冲神经网络模型为基础,采用圆映射的脉冲编码理论将脉冲序列转化为符号序列;同时,以符号序列的距离函数作为语音识别的相似度函数,结合SNN计算能力和实时性强等优势,对语音识别问题进行了初步探讨和研究。实验结果表明,本文提出的特别的研究方法是可行的,具有深入研究的价值。
In this paper, a method of speech recognition based on Spiking Neural Networks（SNNs） is presented. Based on the H-H spiking neural model, this method can transform a sequence of spikes to a symbolic sequence with the circle map spiking coding. Meanwhile we use the distance function of the symbolic sequence as the similarity function of speech recognition, consider the merits of SNN＇s strong computing capability and real-timeness, and perform an initial study of the speech recognition problem. The experiment shows that this method is feasible and deserves an in-depth research.
出处
《计算机工程与科学》
CSCD
2008年第4期139-141,共3页
Computer Engineering & Science
关键词
脉冲神经网络
语音识别
H—H方程
圆映射
spiking neural networks
speech recognition
H-H equation
circle map
