Exploration of diverse intelligent approaches in speech recognition systems

Abstract

Artificial Intelligence revolutionizes the industrial sector to the greater extent towards the era of smart world. Real time automatic speech recognition system is on greater demand for the past few years in most of the embedded devices and smart phone applications. Research on automatic speech recognition is quite challenging due to the complication of environmental noises especially with the non stationary one. Machine learning based robust models are developed widely for speech recognition applications in the past decades. Now the researches mostly focused on deep learning approaches in order to improve the performance and better results. The complexity in designing separate feature extraction steps and classification models in the earlier models are eliminated in the deep learning models. This research article presents the detailed view of various research models developed for the application of automatic speech recognition, its advantages and also the various deep learning frame works for exploring future works.