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Apollo: An Interactive Environment for Generating Symbolic Musical Phrases using Corpus-based Style Imitation

arXiv 2504.14055 ↗First posted 18 Apr 2025cs.HC cs.LG cs.SDcited by 0

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Abstract (arXiv)

With the recent developments in machine intelligence and web technologies, new generative music systems are being explored for assisted composition using machine learning techniques on the web. Such systems are built for various tasks such as melodic, harmonic or rhythm generation, music interpolation, continuation and style imitation. In this paper, we introduce Apollo, an interactive music application for generating symbolic phrases of conventional western music using corpus-based style imitation techniques. In addition to enabling the construction and management of symbolic musical corpora, the system makes it possible for music artists and researchers to generate new musical phrases in the style of the proposed corpus. The system is available as a desktop application. The generated symbolic music materials, encoded in the MIDI format, can be exported or streamed for various purposes including using them as seed material for musical projects. We present the system design, implementation details, discuss and conclude with future work for the system.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 23 references that are in the map. First posted on arXiv 18 Apr 2025.

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References · 9

  1. 2018A Hierarchical Latent Vector Model for Learning Long-Term Structure in Musiccited by 131
  2. 2016DeepBach: a Steerable Model for Bach Chorales Generationcited by 91
  3. 2017Deep Learning Techniques for Music Generation -- A Surveycited by 49
  4. 2016Music transcription modelling and composition using deep learningcited by 36
  5. 2018A Functional Taxonomy of Music Generation Systemscited by 31
  6. 2014AI Methods in Algorithmic Composition: A Comprehensive Surveycited by 12
  7. 2016The Machine Learning Algorithm as Creative Musical Toolcited by 8
  8. 2019A Minimal Template for Interactive Web-based Demonstrations of Musical Machine Learningcited by 4
  9. 2020New interfaces for musical expressioncited by 2

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