MUSIC
BIGDATA
Real performances.
Better data.
MusicBigData is developing professional music datasets built from real performances, studio recordings and human musical expertise — structured for artificial intelligence, machine learning, research and music technology.
A recording contains more information than the notes that were played.
Timing, dynamics, articulation, phrasing, velocity, tuning, microtiming, interaction between musicians, instrument character, room response and production decisions are all part of a real musical performance. MusicBigData is being designed to preserve and describe those relationships rather than reducing music to an anonymous audio file.
From studio performance to machine-readable music.
Human Performance
Professionally recorded performances created by real musicians and engineers.
Isolated Sources
Individual instruments, microphones, takes, stems and complete mixes where available.
Musical Ground Truth
Notes, timing, velocity and musical events represented in structured form.
Human Expertise
Musically meaningful labels created and reviewed by people who understand music and audio.
Context
Instrument, tempo, key, performance, recording, production and technical information.
Dataset Production
Purpose-built recordings and annotations created for specific AI and research requirements.
Not scraped.
Produced.
Human music.
Structured for machines.
MusicBigData.com is currently in development as a B2B music-data platform for AI companies, research teams and music-technology developers requiring professionally produced, structured and human-informed training data.