pitchfinder

A compilation of pitch detection algorithms for Javascript. Supports both the browser and node.

A note on versions

This library previous consisted of a single script tag to be included in the browser. I'm deprecating that version and replacing it with a new, npm/babel version. If you have been using the old version, please check out the legacy branch, which consists of the old code. However, I will not be supporting it going forwards. Version 2 is bringing many improvements, unit tests, and more.

Provided pitch-finding algorithms

• YIN - The best balance of accuracy and speed, in my experience. Occasionally provides values that are wildly incorrect.
• AMDF - Slow and only accurate to around +/- 2%, but finds a frequency more consistenly than others.
• Dynamic Wavelet - Very fast, but struggles to identify lower frequencies.
• YIN w/ FFT (coming soon)
• Goertzel (coming soon)
• MacLeod (coming soon)

Installation

npm install --save pitchfinder

Usage

Finding the pitch of a wav file in node

All pitchfinding algorithms provided operate on Float32Arrays. To find the pitch of a wav file, we can use the wav-decoder library to extract the data into such an array.

const fs = require("fs");
const WavDecoder = require("wav-decoder");
const Pitchfinder = require("pitchfinder");

// see below for optional constructor parameters.
const detectPitch = new Pitchfinder.YIN();

const buffer = fs.readFileSync(PATH_TO_FILE);
const decoded = WavDecoder.decode(buffer); // get audio data from file using `wav-decoder`
const float32Array = decoded.channelData[0]; // get a single channel of sound
const pitch = detectPitch(float32Array); // null if pitch cannot be identified

Finding the pitch of a WebAudio AudioBuffer in the browser

This assumes you are using an npm-compatible build system, like Webpack or Browserify, and that your target browser supports WebAudio. Ample documentation on WebAudio is available online, especially on Mozilla's MDN.

const Pitchfinder = require("pitchfinder");
const detectPitch = Pitchfinder.AMDF();

const myAudioBuffer = getAudioBuffer(); // assume this returns a WebAudio AudioBuffer object
const float32Array = myAudioBuffer.getChannelData(0); // get a single channel of sound
const pitch = detectPitch(float32Array); // null if pitch cannot be identified

Finding a series of pitches

Set a tempo and a quantization interval, and an array of pitches at each interval will be returned.

const Pitchfinder = require("pitchfinder");
const detectPitch = Pitchfinder.YIN();

const frequencies = Pitchfinder.frequencies(detectPitch, float32Array, {
  tempo: 130, // in BPM, defaults to 120
  quantization: 4, // samples per beat, defaults to 4 (i.e. 16th notes)
});

// or use multiple detectors for better accuracy at the cost of speed.
const detectors = [detectPitch, Pitchfinder.AMDF()];
const moreAccurateFrequencies = Pitchfinder.frequencies(detectors, float32Array, {
  tempo: 130, // in BPM, defaults to 120
  quantization: 4, // samples per beat, defaults to 4 (i.e. 16th notes)
});

Configuration

All detectors

• sampleRate - defaults to 44100

YIN

• threshold - used by the algorithm
• probabilityThreshold - don't return a pitch if probability estimate is below this number.

AMDF

• minFrequency - Lowest frequency detectable
• maxFrequency - Highest frequency detectable
• sensitivity
• ratio

Dynamic Wavelet

no special config

Todo

• Integrate with teoria or another music theory tool to add more intelligent parsing.
• Note-onsite algorithms.
• Enable requiring of single detectors.

Thanks

Several of these algorithms were ported from Jonas Six's excellent TarsosDSP library (written in Java). If you're looking for a far deeper set of tools than this, check out his work on his website or on Github.

Thanks to Aubio for his YIN code