Real-time Chinese syllable recognition system with hierarchically structured neural network and transputer system

The authors propose a real-time Chinese syllable recognition system with a hierarchical neural network and a transputer system. The hierarchical neural network is composed of a type of classification network and three recognition networks. The Chinese syllable set is partitioned into a group of sub-sets. The classification network identifies the subset to which the input syllable belongs, and the recognition networks recognize the syllable in the subset. The experimental results show that the scale of the neural network was greatly reduced and the memory of neural network was strengthened, and higher recognition accuracy was obtained. A fast effective nonlinear time alignment method and an improved training method are proposed. The real-time system hardware is described