Emotion Recognition from Helpdesk Messages

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F15%3APU115668" target="_blank" >RIV/00216305:26220/15:PU115668 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/7382448" target="_blank" >https://ieeexplore.ieee.org/document/7382448</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICUMT.2015.7382448" target="_blank" >10.1109/ICUMT.2015.7382448</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Emotion Recognition from Helpdesk Messages

Popis výsledku v původním jazyce

This paper describes system for emotion recognition which can be used to determine the priority of messages on the first level of helpdesk services. An algorithm used in this paper uses artificial intelligence (SVM classifier) and can recognize 5 different emotions. The used emotional classes were based on acoustic model which was inspired by acoustic emotion recognition research works. The proposed system has evaluated 5 classifiers and identifies a dominant emotion class. This work also describes a small database which was created on the basis of the selected helpdesk messages. The database was used in training and testing of the mentioned classifier. Success of classifier achieved in this work is 76.63% and impact of the proposed optimization methods on the final model accuracy has been proven.

Název v anglickém jazyce

Emotion Recognition from Helpdesk Messages

Popis výsledku anglicky

This paper describes system for emotion recognition which can be used to determine the priority of messages on the first level of helpdesk services. An algorithm used in this paper uses artificial intelligence (SVM classifier) and can recognize 5 different emotions. The used emotional classes were based on acoustic model which was inspired by acoustic emotion recognition research works. The proposed system has evaluated 5 classifiers and identifies a dominant emotion class. This work also describes a small database which was created on the basis of the selected helpdesk messages. The database was used in training and testing of the mentioned classifier. Success of classifier achieved in this work is 76.63% and impact of the proposed optimization methods on the final model accuracy has been proven.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

<a href="/cs/project/FR-TI4%2F151" target="_blank" >FR-TI4/151: Výzkum a vývoj technologie pro detekci emocí v nestrukturovaných datech</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2015 7th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

ISBN

978-1-4673-9282-2

ISSN

—

e-ISSN

—

Počet stran výsledku

4

Strana od-do

310-313

Název nakladatele

Neuveden

Místo vydání

Neuveden

Místo konání akce

Brno

Datum konání akce

6. 10. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000380551300054