Logo des Repositoriums
 

Exploring an Architecture of an Adaptable GenAI-Driven Multimodal User Interface for Third-Party Systems

Kurzanzeige
dc.contributor.authorMünch, Tobias
dc.contributor.authorGaedke, Martin
dc.date.accessioned2024-08-21T11:08:33Z
dc.date.available2024-08-21T11:08:33Z
dc.date.issued2024
dc.description.abstractNowadays, Generative Artificial Intelligence (GenAI) can outperform humans in creative professions, such as design. As a result, GenAI attracted a lot of attention from researchers and industry. However, GenAI could used to augment humans with a multimodal user interface, as proposed by Ben Shneiderman in his recent work on Human-Centred Artificial Intelligence (HCAI). Most studies of HCAI have mainly focused on greenfield projects. In contrast to existing research, we describe a brownfield software architecture approach with a loosely coupled GenAI-driven multimodal user interface that combines human interaction with third-party systems. A domain-specific language for user interaction connects natural language and signals of the existing system through GenAI. Our proposed architecture enables research and industry to provide user interfaces for existing software systems that allow hands-free interaction.en
dc.identifier.doi10.18420/muc2024-mci-ws09-128
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/44270
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofMensch und Computer 2024 - Workshopband
dc.relation.ispartofseriesMensch und Computer
dc.rightshttp://purl.org/eprint/accessRights/RestrictedAccess
dc.rights.urihttp://purl.org/eprint/accessRights/RestrictedAccess
dc.titleExploring an Architecture of an Adaptable GenAI-Driven Multimodal User Interface for Third-Party Systemsen
dc.typeText/Workshop Paper
gi.conference.date1.-4. September 2024
gi.conference.locationKarlsruhe
gi.conference.sessiontitleMCI-WS09: Workshop on Generative Artificial Intelligence in Interactive Systems: Experiences from the Community

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild
Name:
muc2024-mci-ws09-128.pdf
Größe:
396.02 KB
Format:
Adobe Portable Document Format
Herunterladen

Sammlungen

Workshopband MuC 2024