Awesome
Basic Pitch is a Typescript and Python library for Automatic Music Transcription (AMT), using lightweight neural network developed by Spotify's Audio Intelligence Lab. It's small, easy-to-use, and npm install
-able.
Basic Pitch may be simple, but it's is far from "basic"! basic-pitch
is efficient and easy to use, and its multipitch support, its ability to generalize across instruments, and its note accuracy competes with much larger and more resource-hungry AMT systems.
Provide a compatible audio file and basic-pitch will generate a MIDI file, complete with pitch bends. Basic pitch is instrument-agnostic and supports polyphonic instruments, so you can freely enjoy transcription of all your favorite music, no matter what instrument is used. Basic pitch works best on one instrument at a time.
Research Paper
This library was released in conjunction with Spotify's publication at ICASSP 2022. You can read more about this research in the paper, A Lightweight Instrument-Agnostic Model for Polyphonic Note Transcription and Multipitch Estimation.
If you use this library in academic research, consider citing it:
@inproceedings{2022_BittnerBRME_LightweightNoteTranscription_ICASSP,
author= {Bittner, Rachel M. and Bosch, Juan Jos\'e and Rubinstein, David and Meseguer-Brocal, Gabriel and Ewert, Sebastian},
title= {A Lightweight Instrument-Agnostic Model for Polyphonic Note Transcription and Multipitch Estimation},
booktitle= {Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
address= {Singapore},
year= 2022,
}
Demo
If, for whatever reason, you're not yet completely inspired, or you're just like so totally over the general vibe and stuff, checkout our snappy demo website, basicpitch.io, to experiment with our model on whatever music audio you provide!
Relation to its Python sibling
This library is intended to be 100% compatible with feature parity to its Python sibling, basic-pitch. To that end, please open an issue in the Python library when contributing a change in this library that affects the input features or output.
Usage
To add to your project, run
yarn add @spotify/basic-pitch
From there you can look at src/inference.test.ts
for examples of how to use Basic Pitch. To summarize how to use it,
const audioCtx = new AudioContext();
let audioBuffer = undefined;
audioCtx.decodeAudioData(
fs.readFileSync(/* Path to audio file */),
async (_audioBuffer: AudioBuffer) => {
audioBuffer = _audioBuffer;
},
() => {},
);
while (audioBuffer === undefined) {
await new Promise(r => setTimeout(r, 1));
}
const basicPitch = new BasicPitch(model);
await basicPitch.evaluateModel(
audioBuffer as unknown as AudioBuffer,
(f: number[][], o: number[][], c: number[][]) => {
frames.push(...f);
onsets.push(...o);
contours.push(...c);
},
(p: number) => {
pct = p;
},
);
const notes = noteFramesToTime(
addPitchBendsToNoteEvents(
contours,
outputToNotesPoly(frames, onsets, 0.25, 0.25, 5),
),
);
You can then use notes
in your application however you wish!
Scripts
yarn build
: CommonJS Modules (/cjs
), and ESModule (/esm
) from the source using the TypeScript Compiler.yarn lint
: Lint all source files via ESLint.yarn test
: Run all tests via Jest.yarn commit
: Create a commit, correctly formatted using commitizen.yarn release
: Trigger a release based on your commit messages using semantic-release.
Continuous Integration / Publishing
CI is enabled via github actions.
commitizen, semantic-release, and conventional-changelog are all enabled by default. If you use yarn commit
to format your commit messages, semantic-release will figure out what the next release of your library should be and will publish it to npm on every merge to master.
Model Input
Supported Audio Codecs
basic-pitch
accepts all sound files that are compatible with AudioBuffer including:
.mp3
.ogg
.wav
.flac
Mono Channel Audio Only
While you may use stereo audio as an input to our model, at prediction time, the channels of the input will be down-mixed to mono, and then analyzed and transcribed.
File Size/Audio Length
This model can process any size or length of audio, but processing of larger/longer audio files could be limited by your machine's available disk space. To process these files, we recommend streaming the audio of the file, processing windows of audio at a time.
Sample Rate
Input audio maybe be of any sample rate, however, all audio will be resampled to 22050 Hz before processing.
Contributing
Contributions to basic-pitch
are welcomed! See CONTRIBUTING.md for details.
Copyright and License
basic-pitch
is Copyright 2022 Spotify AB.
This software is licensed under the Apache License, Version 2.0 (the "Apache License"). You may choose either license to govern your use of this software only upon the condition that you accept all of the terms of either the Apache License.
You may obtain a copy of the Apache License at:
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the Apache License or the GPL License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the Apache License for the specific language governing permissions and limitations under the Apache License.