Abstract
The main objective of this project is to extend software usability testing through human facial expression recognition in software engineering. Measuring the satisfaction of software using questionnaires may be misleading due to the difficulties in expressing their satisfaction through natural language. Therefore, this project proposes to extend the usability testing with emotion recognition based on multimodal inputs by defining test scenarios with required emotional state distinction on the scenarios. This project is equipped with a real-time human expression recognition software which displays the emotion detected on the screen. Example of the emotions are “happy”, “sad”, “angry”, “neutral” and so on. The method applied in this project is a convolutional neural network (CNN). CNN will be constructed with Keras using TensorFlow backend. All the process of analysis will be done using Spyder IDE using Python as the programming language. The library such as TensorFlow and sklearn will be imported for this building of this project. Each prediction will be visualized as a line graph. The facial expression detection should be able to accurately tell the emotion of the user throughout the usability test and developers will be able to make improvements based on the results.
Keywords: Network, deep learning, expression recognition, real-time facial expression, software engineering, usability test
Authors
Arthur Loh Chuan Xing [1] ; Chaw Jun Kit [2]
[1][2] Faculty of Computing and Information Technology, Tunku Abdul Rahman University of Management and Technology, Kuala Lumpur, Malaysia
[1] arthur-lcx-wp16@student.tarc.edu.my ; [2] chawjk@tarc.edu.my
Cite Me
Plain Text:
L.C.X.Arthur, J.K.Chaw, "Real-Time Human Facial Expression Recognition for Extended Software Usability Testing," International Conference on Digital Transformation and Applications (ICDXA) 2020, 2020, pp. 184-190, doi: https://doi.org/10.56453/icdxa.2020.1023.
BibTex:
@INPROCEEDINGS{ICDXA2020T402,
author={Arthur, Loh Chuan Xing and Chaw, Jun Kit},
booktitle={International Conference on Digital Transformation and Applications (ICDXA) 2020},
title={Real-Time Human Facial Expression Recognition for Extended Software Usability Testing},
year={2020},
volume={},
number={},
pages={184-190},
doi={https://doi.org/10.56453/icdxa.2020.1023}}
