Test Accuracy Improvement in Spoken Digit Recognition Using Convolutional Neural Networks

Abstract

Now-a-days speech recognition plays an important role in identifying spoken words of any specific person. There are different speech recognition algorithms such as Hidden Markov model algorithm, Acoustic algorithm. In these algorithms all the data can train automatically and models them as frames to recognize speech. In this study, the spoken digit recognition using neural network (NN) and convolutional neural network (CNN) techniques were utilized and implemented with the help of Python software 3.7.3. It is noticed that the test accuracy is improved when spoken digit recognition using CNN.