• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Scopus
  4. Expanding the HAISP Dataset: AI's Impact on Songwriting Across Two AI Song Contests
 
  • Details
  • Full
Options
2025
Conference Paper
Title

Expanding the HAISP Dataset: AI's Impact on Songwriting Across Two AI Song Contests

Abstract
As artificial intelligence (AI) continues to shape creative practices, understanding its role in human-AI songwriting remains crucial. This paper expands the Human-AI Song-writing Processes (HAISP) dataset by incorporating data from the 2024 AI Song Contest, building upon the original 2023 dataset. By analyzing new submissions, we provide further insights into AI’s evolving impact on songwriting workflows, creative decision-making, and control. A com-parative study of AI tool usage and participant strategies between the 2023 and 2024 contests reveals shifts in collaboration patterns and tool effectiveness. Additionally, we assess the differences between general-purpose AI systems and personalized, fine-tuned tools, highlighting their impact on creative agency. Our findings offer key design implications for AI-assisted songwriting tools, providing ac-tionable insights for AI developers and music practitioners seeking to enhance co-creative experiences.
Author(s)
Morris, Lidia
University of Washington
Newman, Michele
University of Washington
Tang, Xinya
University of Washington
Singh, Renee
University of Washington
Vélez Vásquez, Marcel
Universiteit van Amsterdam
Leger, Rebecca
Fraunhofer-Institut für Integrierte Schaltungen IIS  
Lee, Jin Ha
University of Washington
Mainwork
26th International Society for Music Information Retrieval Conference, ISMIR 2025. Proceedings  
Conference
International Society for Music Information Retrieval (ISMIR Conference) 2025  
Open Access
File(s)
Download (185.83 KB)
Rights
CC BY 4.0: Creative Commons Attribution
DOI
10.5281/zenodo.17706323
10.24406/publica-6936
Language
English
Fraunhofer-Institut für Integrierte Schaltungen IIS  
  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024