Abstract
The Generative Electronic Dance Music Algorithmic System (GEDMAS) is a generative music system that composes full Electronic Dance Music (EDM) compositions. The compositions are based on a corpus of transcribed musical data collected through a process of detailed human transcription. This corpus data is used to analyze genre-specific characteristics associated with EDM styles. GEDMAS uses probabilistic and 1st order Markov chain models to generate song form structures, chord progressions, melodies and rhythms. The system is integrated with Ableton Live, and allows its user to select one or several songs from the corpus, and generate a 16 tracks/parts composition in a few clicks. Copyright © 2013, Association for the Advancement of Artificial Intelligence. All rights reserved.
Cite
CITATION STYLE
Anderson, C., Eigenfeldt, A., & Pasquier, P. (2013). The Generative Electronic Dance Music Algorithmic System (GEDMAS). In AAAI Workshop - Technical Report (Vol. WS-13-22, pp. 5–8). AI Access Foundation. https://doi.org/10.1609/aiide.v9i5.12649
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