WaivOps Lo-Fi Drums Dataset: Open Audio Resources for Machine Learning in Music

Lo-Fi Drums Dataset

Lo-Fi Drums Dataset is an open audio collection of drum recordings in the style of lo-fi hip hop music. It features 10,000 audio loops provided in uncompressed stereo WAV format, along with paired JSON files containing label data for supervised training of generative AI audio models.

Overview

The dataset was developed using an algorithmic framework to randomly generate audio loops from a customized database of MIDI patterns and one-shot drum samples. Data augmentation included random sample-swapping and reverb modeling to generate unique drum kits, sound effects and acoustic spaces. It is intended for training or fine-tuning AI models with paired labels, adaptable for prompt-driven drum generation and other supervised learning objectives.

The primary purpose of this dataset is to provide accessible content for machine learning applications in music. Potential use cases include text-to-audio, prompt engineering, feature extraction, tempo detection, audio classification, rhythm analysis, music information retrieval (MIR), sound design and signal processing.

Specifications

• 10,000 4-bar audio loops (approximately 37.5 hours)
• 16-bit WAV format
• Tempo range: 50-90 BPM
• Paired label data (WAV + JSON)
• Variational drum patterns
• Subgenre styles (boom bap, chill hop, trip hop, hip hop)

A key map JSON file is provided for referencing and converting MIDI note numbers to text labels. You can update the text labels to suit your preferences.

License

This dataset was compiled by WaivOps, a crowdsourced music project managed by Patchbanks. All recordings have been sourced from verified composers and providers for copyright clearance.

The Lo-Fi Drums Dataset is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).

Additional Info

For audio examples or more information about this dataset, please refer to the GitHub repository.