@picovoice/rhino-react-native

Picovoice Rhino React Native binding

Usage no npm install needed!

<script type="module">
  import picovoiceRhinoReactNative from 'https://cdn.skypack.dev/@picovoice/rhino-react-native';
</script>

README

Rhino Binding for React Native

Rhino Speech-to-Intent Engine

Made in Vancouver, Canada by Picovoice

Rhino is Picovoice's Speech-to-Intent engine. It directly infers intent from spoken commands within a given context of interest, in real-time. For example, given a spoken command "Can I have a small double-shot espresso?", Rhino infers that the user wants to order a drink and emits the following inference result:

{
  "type": "espresso",
  "size": "small",
  "numberOfShots": "2"
}

Rhino is:

  • using deep neural networks trained in real-world environments.
  • compact and computationally-efficient, making it perfect for IoT.
  • self-service. Developers and designers can train custom models using Picovoice Console.

Compatibility

This binding is for running Rhino on React Native 0.62.2+ on the following platforms:

  • Android 4.1+ (API 16+)
  • iOS 10.0+

Installation

To start install be sure you have installed yarn and cocoapods. Then add these two native modules to your react-native project.

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

or

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

Link the iOS package

cd ios && pod install && cd ..

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

AccessKey

All bindings require a valid Picovoice AccessKey at initialization. AccessKeys act as your credentials when using Rhino SDKs. You can create your AccessKey for free. Make sure to keep your AccessKey secret.

To obtain your AccessKey:

  1. Login or Signup for a free account on the Picovoice Console.
  2. Once logged in, go to the AccessKey tab to create one or use an existing AccessKey.

Permissions

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:

<key>NSMicrophoneUsageDescription</key>
<string>[Permission explanation]</string>

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

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

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, _) {
    resolve(true);
    });
}

recordAudioRequest.then((hasPermission) => {
    if(hasPermission){
        // Code that uses Rhino
    }
});

async _requestRecordAudioPermission() {
    const granted = await PermissionsAndroid.request(
    PermissionsAndroid.PERMISSIONS.RECORD_AUDIO,
    {
        title: 'Microphone Permission',
        message: '[Permission explanation]',
        buttonNeutral: 'Ask Me Later',
        buttonNegative: 'Cancel',
        buttonPositive: 'OK',
    }
    );
    return (granted === PermissionsAndroid.RESULTS.GRANTED)
  }

Usage

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

High-Level API

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

The constructor RhinoManager.create will create an instance of a RhinoManager using a context file that you pass to it.

const accessKey = "${ACCESS_KEY}"; // AccessKey obtained from Picovoice Console (https://picovoice.ai/console/)

async createRhinoManager() {
    try{
        this._rhinoManager = await RhinoManager.create(
            accessKey,
            '/path/to/context/file.rhn',
            inferenceCallback);
    } catch (err) {
        // handle error
    }
}

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

The inferenceCallback parameter is a function that you want to execute when Rhino makes an inference. The function should accept a RhinoInference instance.

inferenceCallback(object){
    if (inference.isUnderstood) {
        // do something with:
        // inference.intent - string representing intent
        // inference.slots - Object<string, string> representing the slot values
    }
}

You can override also the default Rhino model file and/or the inference sensitivity. You can set requireEndpoint parameter to false if you do not wish to wait for silence before Rhino infers context. There is also an optional processErrorCallback that is called if there is a problem encountered while processing audio.

These optional parameters can be passed in like so:

const accessKey = "${ACCESS_KEY}"; // AccessKey obtained from Picovoice Console (https://picovoice.ai/console/)

this._rhinoManager = await RhinoManager.create(
    accessKey,
    "/path/to/context/file.rhn",
    inferenceCallback,
    processErrorCallback,
    'path/to/model/file.pv',
    0.25,
    false);

Once you have instantiated a RhinoManager, you can start audio capture and intent inference by calling:

let didStart = await this._rhinoManager.process();

When RhinoManager returns an inference result via the inferenceCallback, it will automatically stop audio capture for you. When you wish to result, call .process() again.

Once your app is done with using RhinoManager, be sure you explicitly release the resources allocated for it:

this._rhinoManager.delete();

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

Low-Level API

Rhino provides low-level access to the inference engine for those who want to incorporate speech-to-intent into an already existing audio processing pipeline.

Rhino is created by passing a context file to its static constructor create:

const accessKey = "${ACCESS_KEY}"; // AccessKey obtained from Picovoice Console (https://picovoice.ai/console/)

async createRhino(){
    try{
        this._rhino = await Rhino.create(accessKey, '/path/to/context/file.rhn');
    } catch (err) {
        // handle error
    }
}

As you can see, in this case you don't pass in an inference callback as you will be passing in audio frames directly using the process function. The RhinoInference result that is returned from process will have up to four fields:

  • isFinalized - true if Rhino has made an inference, false otherwise
  • isUnderstood - null if isFinalized is false, otherwise true if Rhino understood what it heard based on the context or false if it did not
  • intent - null if isUnderstood is not true, otherwise name of intent that were inferred
  • slots - null if isUnderstood is not true, otherwise the dictionary of slot keys and values that were inferred
let buffer = getAudioFrame();

try {
    let inference = await this._rhino.process(buffer);
    // inference result example:
    // if (inference.isFinalized) {
    //     if (inference.isUnderstood) {
    //          console.log(inference.intent)
    //          console.log(inference.slots)
    //     }
    // }
    }
} 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 inference engine, be sure to explicitly release the resources allocated to Rhino:

this._rhino.delete();

Custom Context Integration

To add a custom context to your React Native application you'll need to add the rhn files to your platform projects.

Adding Android Models

Android custom models and contexts must be added to ./android/app/src/main/assets/.

Adding iOS Models

On iOS, contexts can be added anywhere under ./ios, but they must be included as a bundled resource. The easiest way to include a bundled resource in the iOS project is to:

  1. Open XCode.
  2. Either:
  • Drag and Drop the model/keyword file to the navigation tab.
  • Right click on the navigation tab, and click Add Files To ....

This will bundle your models together when the app is built.

Using Custom Context

const accessKey = "${ACCESS_KEY}"

let contextPath: '';
if (Platform.OS === 'android') {
    contextPath = 'context_android.rhn'
} else if (Platform.OS === 'ios') {
    contextPath = 'context_ios.rhn'
} else {
    // handle errors
}

try {
    let rhino = await Rhino.create(accessKey, contextPath);
} catch (e) {
    // handle errors
}

Non-English Contexts

In order to run inference on non-English contexts you need to use the corresponding model file. The model files for all supported languages are available here.

Demo App

Check out the Rhino React Native demo to see what it looks like to use Rhino in a cross-platform app!