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Employee Work Motivation Detection using Image and Audio Processing

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2020
H.P.H. Wathsara, M.L.P.D. Dhananjana, D.A. Nanayakkara, B.B.K.R. Dharmarathne, L.H Sanjeevi Chandrasiri, J.K. Joseph

H P H Wathsara, M L P D Dhananjana, D A Nanayakkara, B B K R Dharmarathne, Sanjeevi L H Chandrasiri and J K Joseph. Employee Work Motivation Detection using Image and Audio Processing. International Journal of Computer Applications 175(31):34-40, November 2020. BibTeX

	author = {H.P.H. Wathsara and M.L.P.D. Dhananjana and D.A. Nanayakkara and B.B.K.R. Dharmarathne and L.H Sanjeevi Chandrasiri and J.K. Joseph},
	title = {Employee Work Motivation Detection using Image and Audio Processing},
	journal = {International Journal of Computer Applications},
	issue_date = {November 2020},
	volume = {175},
	number = {31},
	month = {Nov},
	year = {2020},
	issn = {0975-8887},
	pages = {34-40},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2020920862},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Customer Support Centers have reached their best level now, being the most preferred way of the modern communication world. These centers play a vital role in the telecommunication industry, helping to satisfy customer services and needs at the highest level. The improvement based on these service companies is based on the agents' performance, which will favorably impact customer satisfaction. In past years, researchers have revealed numerous factors about this background nature of support centers and here from this ultimate task seeks to predict the employee performance as the target. It is suggested to implement a detective system based on image processing and audio processing. The support centers fall into complications in supervising many employees in a specific period to measure the current status of the work and the progress level. During the process, the system uniquely identifies each employee to monitor their availability at a specific time, to assess his/her emotion levels, motions accurately. The proposed system will provide a better service to optimize each employee's efficient workflows, investigate agents' satisfaction level, and confirm whether the customers are treated humanely. The facial features, emotional aspects, motion patterns, and voice frequencies are vital in this research.


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Face Detection, Emotion Detection, Motion Detection, Voice Detection