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Audio → MIDI polyphonic transcription
for any pitched instrument:
guitar, bass, vocals, synth, piano. Lightweight (~230 KB) and fast.
Why ONNX (not the pip package)?
The official
basic-pitch
PyPI package depends on
tensorflow<2.15.1
,
which has no Python 3.14 wheels and would conflict with the MAESTRO
backend's torch installation. Spotify ships the same model as a small
ONNX export, which we serve here and run via
onnxruntime
— same model,
no TensorFlow dependency chain.
Architecture
CNN spectrogram encoder + multi-head pitch/onset/note prediction. See the
ICASSP 2022 paper
for details.
License
Apache-2.0
— commercial-use OK.
Usage in MAESTRO
Loaded by
backend/ai/models/basic_pitch.py
via
onnxruntime
; surfaced
in the AI Workstation's
TranscribePanel
under General / Drums / Vocals
mode tabs.
Citation
@inproceedings{2022_BittnerBRME_LightweightNoteTranscription_ICASSP,
title={A lightweight instrument-agnostic model for polyphonic note transcription and multipitch estimation},
author={Bittner, Rachel M. and Bosch, Juan Jos{\'e} and Rubinstein, David and Meseguer-Brocal, Gabriel and Ewert, Sebastian},
booktitle={ICASSP 2022},
year={2022}
}
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