Completing Audio Drum Loops with Symbolic Drum Suggestions

Behzad Haki, Teresa Pelinski, Marina Nieto Giménez, and Sergi Jordà

Proceedings of the International Conference on New Interfaces for Musical Expression

  • Year: 2023
  • Location: Mexico City, Mexico
  • Track: Papers
  • Pages: 236–243
  • Article Number: 34
  • PDF link

Abstract:

Sampled drums can be used as an affordable way of creating human-like drum tracks, or perhaps more interestingly, can be used as a mean of experimentation with rhythm and groove. Similarly, AI-based drum generation tools can focus on creating human-like drum patterns, or alternatively, focus on providing producers/musicians with means of experimentation with rhythm. In this work, we aimed to explore the latter approach. To this end, we present a suite of Transformer-based models aimed at completing audio drum loops with stylistically consistent symbolic drum events. Our proposed models rely on a reduced spectral representation of the drum loop, striking a balance between a raw audio recording and an exact symbolic transcription. Using a number of objective evaluations, we explore the validity of our approach and identify several challenges that need to be further studied in future iterations of this work. Lastly, we provide a real-time VST plugin that allows musicians/producers to utilize the models in real-time production settings.

Citation:

Behzad Haki, Teresa Pelinski, Marina Nieto Giménez, and Sergi Jordà. 2023. Completing Audio Drum Loops with Symbolic Drum Suggestions. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI:

BibTeX Entry:

  @article{nime2023_34,
 abstract = {Sampled drums can be used as an affordable way of creating human-like drum tracks, or perhaps more interestingly, can be used as a mean of experimentation with rhythm and groove. Similarly, AI-based drum generation tools can focus on creating human-like drum patterns, or alternatively, focus on providing producers/musicians with means of experimentation with rhythm. In this work, we aimed to explore the latter approach. To this end, we present a suite of Transformer-based models aimed at completing audio drum loops with stylistically consistent symbolic drum events. Our proposed models rely on a reduced spectral representation of the drum loop, striking a balance between a raw audio recording and an exact symbolic transcription. Using a number of objective evaluations, we explore the validity of our approach and identify several challenges that need to be further studied in future iterations of this work. Lastly, we provide a real-time VST plugin that allows musicians/producers to utilize the models in real-time production settings.},
 address = {Mexico City, Mexico},
 articleno = {34},
 author = {Behzad Haki and Teresa Pelinski and Marina Nieto Giménez and Sergi Jordà},
 booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
 editor = {Miguel Ortiz and Adnan Marquez-Borbon},
 issn = {2220-4806},
 month = {May},
 numpages = {8},
 pages = {236--243},
 title = {Completing Audio Drum Loops with Symbolic Drum Suggestions},
 track = {Papers},
 url = {http://nime.org/proceedings/2023/nime2023_34.pdf},
 year = {2023}
}