react-nativePorcupine - React Native API

  • Wake Word Detection
  • Local Voice Commands
  • Offline Keyword Spotting
  • Always Listening
  • Voice Activation
  • React Native
  • JavaScript
  • Mobile
  • Android
  • iOS

This document outlines how to integrate Porcupine wake word engine within an application using its React Native API.


  • Node
  • yarn or npm
  • CocoaPods
  • Android SDK 16+
  • JDK 8+
  • Xcode 9+

Refer to React Native's environment setup page for specifics on how to prepare your machine for React Native development.


  • React Native 0.62.2+
  • Android 4.1+ (API 16+)
  • iOS 9.0+


To install Porcupine into you React Native project add the following native modules to your project:

yarn add @picovoice/react-native-voice-processor
yarn add @picovoice/porcupine-react-native


npm i @picovoice/react-native-voice-processor --save
npm i @picovoice/porcupine-react-native --save

Link the iOS package

cd ios && pod install && cd ..

NOTE: Due to a limitation in React Native CLI autolinking, these two native modules cannot be included as transitive dependencies. If you are creating a module that depends on porcupine-react-native and/or react-native-voice-processor, you will have to list these as peer dependencies and require developers to install them alongside.


To enable recording with the hardware's microphone, you must first ensure that you have enabled the proper permission on both iOS and Android.

On iOS, open your Info.plist and add the following line:

<string>[Permission explanation]</string>

On Android, open your AndroidManifest.xml and add the following line:

<uses-permission android:name="android.permission.RECORD_AUDIO" />

Finally, in your app JS code, be sure to check for user permission consent before proceeding with audio capture:

let recordAudioRequest;
if (Platform.OS == 'android') {
// For Android, we need to explicitly ask
recordAudioRequest = this._requestRecordAudioPermission();
} else {
// iOS automatically asks for permission
recordAudioRequest = new Promise(function (resolve, _) {
recordAudioRequest.then((hasPermission) => {
// Code that uses Porcupine
async _requestRecordAudioPermission() {
const granted = await PermissionsAndroid.request(
title: 'Microphone Permission',
message: '[Permission explanation]',
buttonNeutral: 'Ask Me Later',
buttonNegative: 'Cancel',
buttonPositive: 'OK',
return (granted === PermissionsAndroid.RESULTS.GRANTED)


The module provides you with two levels of API to choose from depending on your needs.

High-Level API

PorcupineManager provides a high-level API that takes care of audio recording. This class is the quickest way to get started.

Using the constructor PorcupineManager.fromKeywords will create an instance of the PorcupineManager using one or more of the built-in keywords.

async createPorcupineManager(){
this._porcupineManager = await PorcupineManager.fromKeywords(
["picovoice", "porcupine"],
} catch (err) {
// handle error

NOTE: the call is asynchronous and therefore should be called in an async block with a try/catch.

The detectionCallback parameter is a function that you want to execute when Porcupine has detected one of the keywords. The function should accept a single integer, keywordIndex, which specifies which wake word has been detected.

if(keywordIndex === 0){
// picovoice detected
else if (keywordIndex === 1){
// porcupine detected

Available built-in keywords are stored in the constants PorcupineManager.KEYWORDS and Porcupine.KEYWORDS.

To create an instance of PorcupineManager that detects custom keywords, you can use the PorcupineManager.fromKeywordPaths static constructor and provide the paths to the .ppn file(s).

this._porcupineManager = await PorcupineManager.fromKeywords(["/path/to/keyword.ppn"], detectionCallback);

In addition to custom keywords, you can override the default Porcupine model file and/or keyword sensitivities. These optional parameters can be passed in like so:

this._porcupineManager = await PorcupineManager.fromKeywords(
["/path/to/keyword/file/one.ppn", "/path/to/keyword/file/two.ppn"],
[0.25, 0.6]);

Once you have instantiated a PorcupineManager, you can start audio capture and wake word detection by calling:

let didStart = await this._porcupineManager.start();

And then stop it by calling:

let didStop = await this._porcupineManager.stop();

Once the app is done with using PorcupineManager, be sure you explicitly release the resources allocated to Porcupine:


As you may have noticed, there is no need to deal with audio capture to enable wake word detection with PorcupineManager. This is because it uses our @picovoice/react-native-voice-processor module to capture frames of audio and automatically pass it to the wake word engine.

Low-Level API

Porcupine provides low-level access to the wake word engine for those who want to incorporate wake word detection into a already existing audio processing pipeline.

Porcupine also has fromKeywords and fromKeywordPaths static constructors.

async createPorcupine(){
this._porcupine = await Porcupine.fromKeywords(["picovoice"]);
} catch (err) {
// handle error

As you can see, in this case you don't pass in a detection callback as you will be passing in audio frames directly using the process function:

let buffer = getAudioFrame();
try {
let keywordIndex = await this._porcupine.process(buffer);
if (keywordIndex >= 0) {
// detection made!
} catch (e) {
// handle error

For process to work correctly, the audio data must be in the audio format required by Picovoice. The required audio format is found by calling .sampleRate to get the required sample rate and .frameLength to get the required frame size. Audio must be single-channel and 16-bit linearly-encoded.

Finally, once you no longer need the wake word engine, be sure to explicitly release the resources allocated to Porcupine:


Custom Wake Word

You can create custom Porcupine wake word models using Picovoice Console.

Custom Wake Word Integration

To add a custom wake word to your React Native application you'll need to add the ppn file to your platform projects. Android models must be added to ./android/app/src/main/res/raw/, while iOS models can be added anywhere under ./ios, but must be included as a bundled resource in your iOS project. Then in your app code, using the react-native-fs package, retrieve the files like so:

const RNFS = require('react-native-fs');
let wakeWordName = 'keyword';
let wakeWordFilename = wakeWordName;
let wakeWordPath = '';
if (Platform.OS == 'android') {
// for Android, extract resources from APK
wakeWordFilename += '_android.ppn';
wakeWordPath = `${RNFS.DocumentDirectoryPath}/${wakeWordFilename}`;
await RNFS.copyFileRes(wakeWordFilename, wakeWordPath);
} else if (Platform.OS == 'ios') {
wakeWordFilename += '_ios.ppn';
wakeWordPath = `${RNFS.MainBundlePath}/${wakeWordFilename}`;

Non-English Wake Words

In order to detect non-English wake words you need to use the corresponding model file. The model files for all supported languages are available here.

Issue with this doc? Please let us know.