Towards Enhancing Industrial Training Through Conversational AIVise andre og tillknytning
2025 (engelsk)Inngår i: CUI '25: Proceedings of the 7th ACM Conference on Conversational User Interfaces, Association for Computing Machinery (ACM) , 2025Konferansepaper, Poster (with or without abstract) (Fagfellevurdert)
Abstract [en]
Conversational AI (CAI) has proven effective in educational settings, however its potential in industrial training, where higher precision and reliability are required, remains under-explored. This work-in-progress paper proposes a study to examine how AI persona design (Machine vs. Expert Operator) and voice embodiment (Diegetic vs. Disembodied) influence cognitive load, task efficiency, and usability in industrial training. By training a large language model (LLM) on Standard Operating Procedure (SOP) data, this project aims to develop a CAI assistant that provides real-time, easy-to-access information during task execution, in an attempt to enhance training efficiency and reduce reliance on text-heavy manuals through a user-centered approach.
sted, utgiver, år, opplag, sider
Association for Computing Machinery (ACM) , 2025.
Emneord [en]
Natural language interfaces
HSV kategori
Forskningsprogram
Datalogi
Identifikatorer
URN: urn:nbn:se:kth:diva-367516DOI: 10.1145/3719160.3737643ISI: 001539402100008Scopus ID: 2-s2.0-105011598225OAI: oai:DiVA.org:kth-367516DiVA, id: diva2:1984901
Konferanse
7th ACM Conference on Conversational User Interfaces, CUI ’25, July 08–10, 2025, Waterloo, ON, Canada
Merknad
QC 20250729
2025-07-182025-07-182025-12-08bibliografisk kontrollert