Research of emotional state students during test using biometric technology

Andrej Vlasenko

Doctoral dissertation

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Technological sciences, informatic engineering (07T).

The dissertation investigates the issues of creating a computer system that uses voice signal features to determine person’s emotional state. In addition presented system of measuring pupil diameter.The main objects of research include emotion recognition from speech and dynamics of eye pupil size change.The main purpose of this dissertation is employing suitable methodologies and algorithms to automatically process and analyse human voice parameters. Created algorithms can be used in Stress Management System software. The dissertation also focuses on researching the possibilities of identification of speaker’s psychoemotional state: applying the analysis of speaker’s voice parameters and the analysis of dynamics of eye pupil size change.

The dissertation consists of four parts including Introduction, 4 chapters, Conclusions and References.

The introduction reveals the investigated problem, importance of the thesis and the object of research and describes the purpose and tasks of the paper, research methodology, scientific novelty, the practical significance of results examined in the paper and defended statements. The introduction ends in presenting the author’s publications on the subject of the defended dissertation, offering the material of made presentations in conferences and defining the structure of the dissertation.

Chapter 1- the Recommended Biometric Stress Management System founded on the speech analysis. The System can assist in determining the level of negative stress and resolve the problem for lessening it and can help to manage current stressful situation and to minimize future stress by making the level of future need satisfaction more rational.

Chapter 2 investigates the possibilities of detecting trends of microtremor frequency (Pitch phase modulation). Suggested methodology and the algorithm microtremor detect and show that when a person experiences stress, the value microtremor can reach 12 Hz. Besides suggested methodology and the algorithm determine the preparation grade students for the examination and evaluation of knowledge based on his speech analysis.

Chapter 3 investigates the possibilities of detecting trends of voice signal parameters. Suggested methodology and the algorithm voice signal parameters detect and show, that when a person is in anger state Pitch increases by 30-50 percent compared to a neutral state.

Chapter 4 investigates the possibilities of detecting trends of pupil size change depending on person’s psychoemotional state. Suggested methodology and the algorithm detecting psychoemotional state based on measurements pupil size change. Presented hardware system to measure the pupil size change. Shows relationship between pupil size and person's emotional state.

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160×230 mm
124 p.
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