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Talk to me! Toward Speech-based UML Modeling

  • Simon Schwantler
  • , Stefan Klikovits
  • , Haydar Metin
  • , Philip Langer
  • , Dominik Bork*
  • *Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

Abstract

Modelling is a core task in enterprise systems engineering. The use of graphical modelling editors, however, remains cumbersome in general and poses a significant challenge for users with disabilities. Natural language processing (NLP) and intent recognition are at the forefront of making many technologies more accessible and intuitive by allowing users to engage using natural language. This paper presents a natural language interface (NLI) for speech-based UML model interaction that leverages state-of-the-art NLP technologies to enable speech-based modelling. We provide a workflow for the creation of NLIs for modelling editors, a proof-of-concept integration of this approach into the bigUML open-source modelling editor, and an empirical evaluation that shows promising results in intent recognition, the effectiveness of model creation, and usability. Thereby, this paper makes significant contributions towards more natural, inclusive, and accessible modelling.
OriginalspracheEnglisch
TitelThe Practice of Enterprise Modeling - 18th IFIP Working Conference, PoEM 2025, Proceedings
Untertitel18th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modeling (PoEM 2025), Switzerland, Geneva, December 3-5, 2025
Herausgeber*innenHans-Georg Fill, Yves Wautelet, Jolita Ralyté, Jelena Zdravkovic
VerlagSpringer, Cham
Seiten83-101
Seitenumfang19
Auflage1
ISBN (Print)9783032120625
DOIs
PublikationsstatusElektronische Veröffentlichung vor Drucklegung - 28 Nov. 2025

Publikationsreihe

NameLecture Notes in Business Information Processing
Band570 LNBIP
ISSN (Print)1865-1348
ISSN (elektronisch)1865-1356

Wissenschaftszweige

  • 102022 Softwareentwicklung
  • 502050 Wirtschaftsinformatik
  • 102040 Quantencomputing
  • 509026 Digitalisierungsforschung
  • 211928 Systems Engineering
  • 102034 Cyber-Physical Systems
  • 502032 Qualitätsmanagement
  • 102020 Medizinische Informatik
  • 102006 Computer Supported Cooperative Work (CSCW)
  • 102027 Web Engineering
  • 102016 IT-Sicherheit
  • 503015 Fachdidaktik Technische Wissenschaften
  • 102015 Informationssysteme

JKU-Schwerpunkte

  • Digital Transformation

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