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
• DOI: 10.5281/zenodo.11189168 (Link to paper)
• 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:

BibTeX Entry:

  @inproceedings{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},
 doi = {10.5281/zenodo.11189168},
 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}
}