Evaluation of Conversational Agents: Understanding Culture, Context and Environment in Emotion Detection

Simple item page
dc.contributor.authorTeye, Martha T.
dc.contributor.authorMissah, Yaw Marfo
dc.contributor.authorAhene, Emmanuel
dc.contributor.authorTwum, Frimpong
dc.contributor.orcid0000-0002-2370-4700
dc.contributor.orcid0000-0002-2926-681X
dc.contributor.orcid0000-0002-0810-1055
dc.contributor.orcid0000-0002-1869-7542
dc.date.accessioned2023-12-06T14:23:30Z
dc.date.available2023-12-06T14:23:30Z
dc.date.issued2022-02
dc.descriptionAn article published in IEEE Access, Vol. 10, 2022
dc.description.abstractValuable decisions and highly prioritized analysis now depend on applications such as facial biometrics, social media photo tagging, and human robots interactions. However, the ability to successfully deploy such applications is based on their efficiencies on tested use cases taking into consideration possible edge cases. Over the years, lots of generalized solutions have been implemented to mimic human emotions including sarcasm. However, factors such as geographical location or cultural difference have not been explored fully amidst its relevance in resolving ethical issues and improving conversational AI (Artificial Intelligence). In this paper, we seek to address the potential challenges in the usage of conversational AI within Black African society. We develop an emotion prediction model with accuracies ranging between 85% and 96%. Our model combines both speech and image data to detect the seven basic emotions with a focus on also identifying sarcasm. It uses 3-layers of the Convolutional Neural Network in addition to a new Audio-Frame Mean Expression (AFME) algorithm and focuses on model pre-processing and post processing stages. In the end, our proposed solution contributes to maintaining the credibility of an emotion recognition system in conversational AIs.
dc.description.sponsorshipKNUST
dc.identifier.citationIEEE Access, Vol. 10, 2022
dc.identifier.uri10.1109/ACCESS.2022.3153787
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/14671
dc.language.isoen
dc.publisherIEEE Access
dc.titleEvaluation of Conversational Agents: Understanding Culture, Context and Environment in Emotion Detection
dc.typeArticle
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Evaluation_of_Conversational_Agents_Understanding_Culture_Context_and_Environment_in_Emotion_Detection.pdf
Size:
1.12 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed to upon submission
Description:
Download
Collections
Articles