A high performance neural-networks-based speech recognition system
Song Yang, Meng Joo Er, Yang Gao · 2002
A high performance neural-network-based speech recognition system is presented. A new approach towards feature representation for speech recognition, named state transition matrix (STM), is proposed to address temporal varying problem in speech recognition. Using STM, we need only a single-layer perceptron neural network to perform speech recognition. Experimental results show that an overall accuracy of 95% and 87% was achieved for speaker-dependent isolated word recognition and multi-speaker-dependent isolated word recognition, respectively.