Image approach to english digits recognition using deep learning

Fatin Nur Amalina, Zainol and Mohd Zamri, Ibrahim (2022) Image approach to english digits recognition using deep learning. In: IET Conference Proceedings. 2022 Engineering Technology International Conference, ETIC 2022 , 7 - 8 September 2022 , Kuantan, Virtual. pp. 6-11., 2022 (22). ISSN 2732-4494 ISBN 978-183953782-0 (Published)

	Pdf Image approach to english digits recognition using deep learning.pdf Restricted to Repository staff only Download (363kB) | Request a copy
Preview	Pdf Image approach to english digits recognition using deep learning_ABS.pdf Download (49kB) | Preview

Abstract

Despite good progress in speech recognition, various challenges still exist due to differences in how they speak, age, gender, emotions, and dialects when perceived by the ear. There is a proverb “I hear, and I forget; I see, and I remember”. The image would be another solution to recognize what we hear. The main objective of this paper is to investigate the graphic method to learn digit English using the Deep Learning technique. In this work, Mel-frequency cepstral coefficients (MFCC) in the form of an image will be used as input to the system. Convolutional neural network (CNN) will be used to extract features from the image and an artificial neural network (ANN) will be used to classify those features into 10-digit English classes. By using the Speech Command dataset, the performance of the system will be compared with a conventional method that uses MFCC features in the form of a signal. The experiments showed that the image approach improves the recognition rate from 49% to 84%. It can be concluded that image approach can be used as an alternative method for digit recognition.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Artificial neural network; Automatic speech recognition; Convolutional neural network; Deep neural network; Mel frequency cepstral coefficient
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Institute of Postgraduate Studies Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	30 Aug 2024 00:24
Last Modified:	30 Aug 2024 00:24
URI:	http://umpir.ump.edu.my/id/eprint/41957
Download Statistic:	View Download Statistics

Actions (login required)

View Item