The Freesound Loop Dataset and Annotation Tool
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Abstract (arXiv)
Music loops are essential ingredients in electronic music production, and there is a high demand for pre-recorded loops in a variety of styles. Several commercial and community databases have been created to meet this demand, but most are not suitable for research due to their strict licensing. We present the Freesound Loop Dataset (FSLD), a new large-scale dataset of music loops annotated by experts. The loops originate from Freesound, a community database of audio recordings released under Creative Commons licenses, so the audio in our dataset may be redistributed. The annotations include instrument, tempo, meter, key and genre tags. We describe the methodology used to assemble and annotate the data, and report on the distribution of tags in the data and inter-annotator agreement. We also present to the community an online loop annotator tool that we developed. To illustrate the usefulness of FSLD, we present short case studies on using it to estimate tempo and key, generate music tracks, and evaluate a loop separation algorithm. We anticipate that the community will find yet more uses for the data, in applications from automatic loop characterisation to algorithmic composition.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Aug 2020.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 2; 2026: 1.
6 papers.
- 2023LLark: A Multimodal Instruction-Following Language Model for Musiccited by 29
- 2025AudioX: A Unified Framework for Anything-to-Audio Generationcited by 27
- 2024Heterogeneous sound classification with the Broad Sound Taxonomy and Datasetcited by 1
- 2026AudioX-Turbo: A Unified Framework for Efficient Anything-to-Audio Generationcited by 1
- 2022Comparision Of Adversarial And Non-Adversarial LSTM Music Generative Modelscited by 0
- 2025Audio-FLAN: An Instruction-Following Dataset for Unified Audio Understanding and Generation of Speech, Music, and Soundcited by 0
- 2026AudioX-Turbo: A Unified Framework for Efficient Anything-to-Audio Generation10 Jun 2026
- 2025AudioX: A Unified Framework for Anything-to-Audio Generation13 Mar 2025
- 2025Audio-FLAN: An Instruction-Following Dataset for Unified Audio Understanding and Generation of Speech, Music, and Sound23 Feb 2025
- 2024Heterogeneous sound classification with the Broad Sound Taxonomy and Dataset1 Oct 2024
- 2023LLark: A Multimodal Instruction-Following Language Model for Music11 Oct 2023
- 2022Comparision Of Adversarial And Non-Adversarial LSTM Music Generative Models1 Nov 2022