Authors: Mousmita Sarma
Addresses: Department of Electronics and Communication Engineering, Gauhati University, Guwahati, Assam, India
Abstract: Deep neural networks (DNN) are special forms of learning-based structures composed of multiple hidden layers formed by artificial neurons. These are different to the conventional artificial neural networks (ANN) and are accepted as efficient tools for solving emerging real world problems. Recently, DNNs have become a mainstream speech recognition tool and are fast becoming part of evolving technologies emerging as a viable option to replace all other leading tools so far used. ANNs with deep learning which uses a generative, layer by-layer pre-training method for initialising the weights has provided best solution for acoustic modelling for speech recognition. This paper provides a brief description of the current technology related to speech recognition and its slow adoption of DNN-based approaches. Initially, a historical note on the technology development for speech recognition system is given. The later part explains the DNN-based acoustic modelling for speech recognition and recent technology developments reported and the ones available for actual use.
Keywords: speech recognition; artificial neural networks; ANNs; deep neural networks; DNN; acoustic modelling.
International Journal of Intelligent Systems Design and Computing, 2017 Vol.1 No.1/2, pp.71 - 86
Received: 07 Apr 2015
Accepted: 18 May 2015
Published online: 10 Mar 2017 *