Stammdaten

Titel: A Domain Specific Modeling Language for Model-Based Design of Voice User Interfaces
Untertitel:
Kurzfassung:

Designing a voice user interface (VUI) can become more challenging than designing a graphical user interface (GUI). Without visual interaction elements, a user can be less bound to predefined interaction regulations and restrictions. Concrete user requests and system responses in a dialog strongly depend on the initial intention of the user and the user’s utterances during the dialog, to which the voice-based system has to respond. The aim of this paper is to present an intention-oriented approach to the design of VUIs. This is achieved in particular by defining and applying RIML, a domain specific modeling language, which enables VUI designers to create platform-independent inten-tion models. A RIML model includes to which requests a VUI should respond to, what intentions are involved, how the system handles user requests and responses, and what to do in case of misunderstanding or failure. Based on a RIML model, a voice-based system with a model driven architecture is able to communicate flexibly via its VUI with the user.

Schlagworte: Domain Specific Modeling Language, Intention Modeling, Active Assistance, Voice User Interface, Voice-Based System
Publikationstyp: Beitrag in Proceedings (Autorenschaft)
Erscheinungsdatum: 07.11.2020 (Online)
Erschienen in: ER Forum, Demo and Posters 2020 co-located with 39th International Conference on Conceptual Modeling (ER 2020)
ER Forum, Demo and Posters 2020 co-located with 39th International Conference on Conceptual Modeling (ER 2020)
zur Publikation
 ( CEUR Workshop Proceedings (CEUR-WS.org); J. Michael, V. Torres )
Titel der Serie: -
Bandnummer: -
Erstveröffentlichung: Ja
Version: -
Seite: S. 3 - 16

Versionen

Keine Version vorhanden
Erscheinungsdatum: 07.11.2020
ISBN (e-book): -
eISSN: 1613-0073
DOI: -
Homepage: http://ceur-ws.org/Vol-2716/
Open Access
  • Online verfügbar (Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Artificial Intelligence und Cybersecurity
Universitätsstr. 65-67
A-9020 Klagenfurt
Österreich
  -993705
   aics-office@aau.at
https://www.aau.at/en/aics/
zur Organisation
Universitätsstr. 65-67
AT - A-9020  Klagenfurt

Kategorisierung

Sachgebiete
Forschungscluster
  • Humans in the Digital Age
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: II)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Intelligente Systeme und Wirtschaftsinformatik

Kooperationen

Keine Partnerorganisation ausgewählt

Beiträge der Publikation

Keine verknüpften Publikationen vorhanden