Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice

Due to the migration megatrend, efficient and effective second-language acquisition is vital. One proposed solution involves AI-enabled conversational agents for person-centered interactive language practice. We present results from ongoing action research targeting quality assurance of proprietary generative dialog models trained for virtual job interviews. The action team elicited a set of 38 requirements for which we designed corresponding automated test cases for 15 of particular interest to the evolving solution. Our results show that six of the test case designs can detect meaningful differences between candidate models. While quality assurance of natural language processing applications is complex, we provide initial steps toward an automated framework for machine learning model selection in the context of an evolving conversational agent. Future work will focus on model selection in an MLOps setting.

NATURVETENSKAP Data- och informationsvetenskap Programvaruteknik hsv//swe
NATURAL SCIENCES Computer and Information Sciences Software Engineering hsv//eng
action research
AI quality
conversational agent
generative dialog model
requirements engineering
software testing
Learning algorithms
Natural language processing systems
Quality assurance
Software agents
Conversational agents
Dialogue models
Megatrends
Model Selection
Requirement engineering
Software testings
Swedishs

Bengtsson, J.Lund University, Sweden (författare)
Osterling, H.Lund University, Sweden (författare)
Hagelborn, A.NordAxon AB, Sweden (författare)
Gagner, IsabellaRISE,Mobilitet och system (författare)
Tomaszewski, PiotrRISE,Mobilitet och system(Swepub:ri)piotrto@ri.se (författare)
RISEMobilitet och system (creator_code:org_t)

Ingår i:Proceedings - 1st International Conference on AI Engineering - Software Engineering for AI, CAIN 2022New York, NY, USA : Institute of Electrical and Electronics Engineers Inc., s. 22-329781450392754

Av författaren/redakt...: Borg, Markus; Bengtsson, J.; Osterling, H.; Hagelborn, A.; Gagner, Isabella; Tomaszewski, Pio ...

Om ämnet

NATURVETENSKAP: NATURVETENSKAP; och Data och informa ...; och Programvarutekni ...

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