license: mit
library_name: drum_dynamics
tags:
- drums
- midi
- velocity
- dynamics
- music
- transformer
- mixture-density-network
datasets:
- e-gmd
metrics:
- mae
- rmse
- nll
Dynamics Needed — MDN transformer velocity model
Version: 0.1.0
Transformer with a mixture-density-network (MDN) head that predicts a distribution over per-note velocities ("dynamics") for MIDI drum tracks. Trained on the Expanded Groove MIDI Dataset (E-GMD). Part of the Dynamics Needed thesis project.
Intended use
Given a MIDI drum track with flat/undynamic velocities, sample or read out a "best-fitting" velocity per note to restore human-like dynamics. Unlike the LightGBM baseline, this model captures velocity uncertainty.
Training data
E-GMD (Expanded Groove MIDI Dataset), evaluated on the held-out test split.
Metrics (test split)
| metric | value |
|---|---|
| Native NLL | 4.473 |
| Discretized NLL | 3.132 |
| Deterministic readout — MAE | 19.695 |
| Deterministic readout — RMSE | 26.641 |
| Sampled — Wasserstein-1 | 2.948 |
| Sampled — histogram intersection | 0.921 |
Use the deterministic readout for accuracy/ranking; sample from the predicted distribution to restore human-like variance.
Limitations
Published as a versioned research artifact, not a final production model.
- Point-vs-sample trade-off. Sampling restores the dynamic spread that a point estimate flattens, but raises MAE and lowers note-by-note ranking correlation. Pick the readout to match the use case.
- Absolute-loudness generalization gap. On unseen drummers, MAE degrades (~19 → ~28) and the sampled distribution shifts low — a player's overall loudness is not inferable from structure alone. Relative dynamics transfer; absolute level does not.
- Known data artifact. E-GMD's multi-kit rendering remaps pads to different
voices per kit, biasing some per-voice results; a single-kit rebuild is a
pending fix. See the project's
docs/methodology/kit-remapping-artifact.md. - No listening test yet. Numbers here are offline metrics; perceptual A/B validation is future work.
License
Set to mit by default — change to match the thesis's chosen license before
publishing.