Speech recognition using deep neural network - recent trends. (2017)

• Record Type: Journal Article
• Authors: Sarma, Mousmita
• Is Part Of: International journal of intelligent systems design and computing. Volume 1:Number 1/2(2017)
• Page Start: 71
• Page End: 86
• Publication Date: 2017
• Subjects: speech recognition -- artificial neural networks -- ANNs -- deep neural networks -- DNN -- acoustic modelling; Artificial intelligence -- Periodicals; Human-computer interaction -- Periodicals; 006.3
• Languages: English
• ISSNs: 2052-8477

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.