DNN based continuous speech recognition system of Punjabi language on Kaldi toolkit

摘要

This paper demonstrates the effect of incorporating Deep Neural Network techniques in speech recognition systems. Speech recognition through hybrid Deep Neural Networks on the Kaldi toolkit for the Punjabi language is implemented. Performance of the automatic speech recognition system drastically improves using DNN, and further Karel's DNN model gives better recognition performance as compared to Dan's DNN model. Out of MFCC and PLP features, the MFCC feature gives better results. The triphone model gives a lower word error rate than the monophone model, and 3-g gives a lower word error rate as compared to a 2-g model on the Kaldi toolkit for the continuous Punjabi speech recognition system.