A Speech Recognition Method Using Competitive and Selective Learning Neural Networks - Hu Guangrui Xu Xiong Yan Yonghong (Tongxin xuebao)
In this paper,a basic principle called the equidistortion principle for vector clustering is theoretically derived by using Gersho’s asymptotic theory,and a new competitive learning algorithm is prorosed with a selection mechanism,called the CLS（Competitive and Selective Learning）algorithm.Because the selection mechanism enables the system to escape from local minima,the proposed algorithm can obtain better performance without a particular initialization procedure.A new neural network algorithm with competitive learning and multiple safe rejection schemes are proposed in the context of parallel,self organizing,hierarchical neural networks（PSHNN）.The input of PSHNN is a subset of the output scores of HMM.The experimental results indicate that the recognition ability of the method based on competitive learning neural network is higher than that of the traditional HMM method.