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A Generative AI-Based Approach to Support Automated Utterance Generation for Different Conversational Contexts within AAC Systems
Konadl, Daniel (2024) A Generative AI-Based Approach to Support Automated Utterance Generation for Different Conversational Contexts within AAC Systems. In: International Conference on Information Systems (ICIS 2024), 15.12.2024 - 18.12.2024, Bangkok, Thailand.Veröffentlichungsdatum dieses Volltextes: 14 Okt 2024 09:30
Konferenz- oder Workshop-Beitrag
DOI zum Zitieren dieses Dokuments: 10.5283/epub.59343
Zusammenfassung
To foster their full integration into the mainstream of society, speech-impaired individuals need to be empowered to use vocal language in various daily life situations. AI-based AAC systems enable speech-impaired individuals to generate completed utterances for use in conversations. However, available solutions exhibit remarkable drawbacks. They do not meet all posed requirements and cannot ...
To foster their full integration into the mainstream of society, speech-impaired individuals need to be empowered to use vocal language in various daily life situations. AI-based AAC systems enable speech-impaired individuals to generate completed utterances for use in conversations. However, available solutions exhibit remarkable drawbacks. They do not meet all posed requirements and cannot provide completed sentences that match the expected styles of formal and informal conversational contexts. Therefore, design requirements for a Generative AI-based utterance composition approach were identified. It has been followed design science research to derive design principles and an instantiation of an AAC prototype that enables context-specific and user-individualizable articulation. The artifact was demonstrated and evaluated with formal and informal interactions commonly performed in the daily routine of visiting a restaurant. In particular, the importance of meeting all specific requirements and employing Generative AI, such as ChatGPT-4.0, to generate both formal and informal utterances, is exemplified.
Beteiligte Einrichtungen
Details
| Dokumentenart | Konferenz- oder Workshop-Beitrag (Paper) | ||||
| Datum | Dezember 2024 | ||||
| Institutionen | Wirtschaftswissenschaften > Institut für Wirtschaftsinformatik > Lehrstuhl für Wirtschaftsinformatik III - Business Engineering (Prof. Dr. Susanne Leist) Informatik und Data Science > Fachbereich Wirtschaftsinformatik > Lehrstuhl für Wirtschaftsinformatik III - Business Engineering (Prof. Dr. Susanne Leist) | ||||
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| Stichwörter / Keywords | Augmentative and Alternative Communication, Generative AI, Conversational Contexts, Automated Utterance Composition, Design Science Research | ||||
| Dewey-Dezimal-Klassifikation | 000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik | ||||
| Status | Veröffentlicht | ||||
| Begutachtet | Ja, diese Version wurde begutachtet | ||||
| An der Universität Regensburg entstanden | Ja | ||||
| URN der UB Regensburg | urn:nbn:de:bvb:355-epub-593431 | ||||
| Dokumenten-ID | 59343 |
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