Word recognition by a parallel-branch subunit model based on misrecognized data in semi-continuous HMM

We propose a parallel-branch subunit model in semicontinuous HMM for improved initialization and training in word recognition. We obtain the model by adding a new subunit branch based on misrecognized data in training to the previous parallel branches for that subunit. Simulation results show that this proposed model is efficient and gives good recognition performance in word recognition.