Program for Person’s Emotional State Recognition

Student: Rubinshteyn Viktor

Educational Programme: System and Software Engineering (Master)

Year of Graduation: 2019

The problem of Automatic Emotion Recognition (AER) becomes more urgent in the area of human-computer interaction system development. Multimodal analysis of emotions is an extension of the classical AER approaches. It fuses the results of various unimodal emotion recognizers that use the face-expression images and speech records as input data. There are a lot amount of ready-for-use code-libraries for unimodal analysis for different programming languages, but the multimodal recognizers are not available for developers yet. The purpose of this work is to create a JS-library which provides a tool for multimodal human emotion state recognition by a set of face images and speech record.

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses