Application of Deep Learning in Speech Recognition

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Author(s): Rekh Ram Janghel (NIT Raipur, India), Satya Prakash Sahu (NIT Raipur, India), Yogesh Kumar Rathore (NIT Raipur, India), Shraddha Singh (NIT Raipur, India)and Urja Pawar (NIT Raipur, India)
Copyright: 2019
Pages: 13
Source title: Handbook of Research on Deep Learning Innovations and Trends
Source Author(s)/Editor(s): Aboul Ella Hassanien (Cairo University, Egypt), Ashraf Darwish (Helwan University, Egypt)and Chiranji Lal Chowdhary (VIT University, India)
DOI: 10.4018/978-1-5225-7862-8.ch004

Keywords: Artificial Intelligence / Computer Science & IT / Engineering Science Reference / Neural Networks

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Abstract

Speech is the vocalized form of communication used by humans and some animals. It is based upon the syntactic combination of items drawn from the lexicon. Each spoken word is created out of the phonetic combination of a limited set of vowel and consonant speech sound units (phonemes). Here, the authors propose a deep learning model used on tensor flow speech recognition dataset, which consist of 30 words. Here, 2D convolutional neural network (CNN) model is used for understanding simple spoken commands using the speech commands dataset by tensor flow. Dataset is divided into 70% training and 30% testing data. While running the algorithm for three epochs average accuracy of 92.7% is achieved.

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Application of Deep Learning in Speech Recognition

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