Basic Pitch

A lightweight yet powerful audio-to-MIDI converter with pitch bend detection

AI & Machine LearningPythonApache-2.0

Abstract

Basic Pitch is an open-source AI & Machine Learning project. A lightweight yet powerful audio-to-MIDI converter with pitch bend detection. Basic Pitch is a Python library for Automatic Music Transcription (AMT), using lightweight neural network developed by Spotify's Audio Intelligence Lab. It's small, easy-to-use, pip install-able and npm install-able via its sibling repo. It is built using Python, Machine Learning, TypeScript. The complete source code is publicly available on GitHub under the Apache License 2.0, making it a useful reference for students building an AI & Machine Learning mini project or final-year project.

1. Introduction

Basic Pitch is a Python library for Automatic Music Transcription (AMT), using lightweight neural network developed by Spotify's Audio Intelligence Lab. It's small, easy-to-use, pip install-able and npm install-able via its sibling repo.

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.

2. Objective

A lightweight yet powerful audio-to-MIDI converter with pitch bend detection

This project demonstrates how Python, Machine Learning, TypeScript can be applied to a real-world AI & Machine Learning problem.

4. Technology Stack

PythonMachine LearningTypeScript

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

  • Python 3.8 or later
  • pip / virtualenv for dependencies
  • VS Code, PyCharm or Jupyter Notebook
  • Node.js (LTS) and npm / yarn / pnpm
  • VS Code or any code editor
  • Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/spotify/basic-pitch.git
cd basic-pitch

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

  • Deploy the model as a web app with Streamlit, Flask or FastAPI
  • Compare against an additional model and report the metric difference
  • Add explainability (SHAP / Grad-CAM)

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

  1. What dataset does the project use and how was it pre-processed?
  2. Which algorithm / model architecture is used and why was it chosen over alternatives?
  3. How are training and testing data split, and how is overfitting avoided?
  4. Which evaluation metrics (accuracy, precision, recall, F1) are reported and what do they mean here?
  5. How would you deploy this model for real users?

9. Source Code & License

This project is developed by spotify and published on GitHub under the Apache License 2.0. Please follow the license terms and credit the original author when you use or modify this code.

View Source on GitHubDownload ZIP

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