Bach Doodle Dataset
dataset·user contributed symbolic music·active
User-entered melodies and model-generated four-voice harmonizations contributed through the 2019 Bach Doodle.
Verified facts
| Official site | https://magenta.tensorflow.org/datasets/bach-doodle ↗ |
|---|---|
| Geography | United States |
| size | sessions: 8500000 · music years: 6 · compositions: 21600000 |
| scope | Miniature user melodies and Coconet harmonizations with interaction metadata. |
| genres | Bach-style chorale harmonization |
| license | CC BY 4.0 |
| steward | Google LLC |
| creators | Cheng-Zhi Anna Huang; Curtis Hawthorne; Adam Roberts; Monica Dinculescu; James Wexler; Leon Hong; Jacob Howcroft |
| languages | not_applicable |
| modalities | MIDI NoteSequence; JSONL; TFRecord; country-level metadata; feedback metadata |
| geographies | Global |
| access method | Google-hosted JSONL or TFRecord archives and shards. |
| intended uses | music generation; music education; ethnomusicology |
| consent claims | Opt-in contribution described on the official page. |
| related papers | The Bach Doodle: Approachable music composition with machine learning at scale |
| prohibited uses | No specific prohibited uses stated beyond license compliance. |
| annotation method | Automatic session, key, timing, country-code, playback and feedback metadata. |
| collection method | Users created melodies in a web Doodle and could rate and contribute them to a public dataset. |
| provenance claims | Official page states users could choose to contribute compositions to the public dataset. |
| current availability | Official downloads active. |
| commercial use limits | No dataset-level noncommercial restriction stated; attribution required. |
| us market scope basis | Publicly available or materially used in US-facing music/audio-AI research. |
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