pitchfinder

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

Provided pitch-finding algorithms

- YIN - The best balance of accuracy and speed, in my experience. Occasionally provides values that are wildly incorrect.
- Mcleod - Also works well. Some have reported better performance on lower frequencies.
- 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)_

Installation

npm install --save pitchfinder

Usage

$3

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.

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

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

const buffer = fs.readFileSync(PATH_TO_FILE);
const decoded = WavDecoder.decode.sync(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
`

$3

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.

`javascript
import * as Pitchfinder from "pitchfinder";

const myAudioBuffer = getAudioBuffer(); // assume this returns a WebAudio AudioBuffer object
const float32Array = myAudioBuffer.getChannelData(0); // get a single channel of sound

const detectPitch = Pitchfinder.AMDF();
const pitch = detectPitch(float32Array); // null if pitch cannot be identified
`

$3

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

`javascript
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

$3

- sampleRate - defaults to 44100

$3

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

$3

- bufferSize - The expected buffer size in samples. Defaults to 1024.
- cutoff - Defines the relative size the chosen peak (pitch) has. 0.93 means: choose the first peak that is higher than 93% of the highest peak detected. 93% is the default value used in the Tartini user interface.

$3

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

$3

_no special config_

Note

If you'd like a version that uses compiled C++ code and runs much faster, check out this repo. However, it will not work in the browser.

Todo

- Integrate with teoria` or another music theory tool to add more intelligent parsing.
- Note-onset 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