Emotion Detection Using Machine Learning: A Study on Human Computer Interaction

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F25%3A50022497" target="_blank" >RIV/62690094:18450/25:50022497 - isvavai.cz</a>

Výsledek na webu

<a href="https://ojs.istp-press.com/jait/article/view/708" target="_blank" >https://ojs.istp-press.com/jait/article/view/708</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.37965/jait.2025.0708" target="_blank" >10.37965/jait.2025.0708</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Emotion Detection Using Machine Learning: A Study on Human Computer Interaction

Popis výsledku v původním jazyce

Emotion is a psychological state of mind that is closely related to various sensations, such as happiness, excitement, neutrality, anger, and frustration. In the modern technological era, emotions play a crucial role in understanding human behavior and motivations. They also have a significant impact on human-computer interactions. If machines can understand human emotions, it would be a remarkable advancement in natural language processing, particularly in the domain of sentiment analysis. Humans experience a wide range of emotions that can change over time. If machines could interpret these emotions and adapt their interactions accordingly, it would greatly enhance the ease and effectiveness of communication between humans and machines. In our study, we employed intelligent algorithms from the field of artificial intelligence, including Naïve Bayes and K-Nearest Neighbor, to interpret human emotions. We utilized speech datasets in the form of audio, sourced from the IEMOCAP database. These algorithms demonstrated the ability to recognize and interpret various emotional states, such as anger, happiness, neutrality, frustration, excitement, and sadness. © The Author(s) 2025.

Název v anglickém jazyce

Emotion Detection Using Machine Learning: A Study on Human Computer Interaction

Popis výsledku anglicky

Emotion is a psychological state of mind that is closely related to various sensations, such as happiness, excitement, neutrality, anger, and frustration. In the modern technological era, emotions play a crucial role in understanding human behavior and motivations. They also have a significant impact on human-computer interactions. If machines can understand human emotions, it would be a remarkable advancement in natural language processing, particularly in the domain of sentiment analysis. Humans experience a wide range of emotions that can change over time. If machines could interpret these emotions and adapt their interactions accordingly, it would greatly enhance the ease and effectiveness of communication between humans and machines. In our study, we employed intelligent algorithms from the field of artificial intelligence, including Naïve Bayes and K-Nearest Neighbor, to interpret human emotions. We utilized speech datasets in the form of audio, sourced from the IEMOCAP database. These algorithms demonstrated the ability to recognize and interpret various emotional states, such as anger, happiness, neutrality, frustration, excitement, and sadness. © The Author(s) 2025.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Journal of Artificial Intelligence and Technology

ISSN

2766-8649

e-ISSN

2766-8649

Svazek periodika

5

Číslo periodika v rámci svazku

May

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

10

Strana od-do

125-134

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-105007613612