3.0.3 • Public • Published

Rhino Binding for Angular

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 would like to order a drink and emits the following inference result:

  "isUnderstood": "true",
  "intent": "orderBeverage",
  "slots": {
    "beverage": "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.


  • Chrome / Edge
  • Firefox
  • Safari


IndexedDB and WebWorkers are required to use Rhino Angular. Browsers without support (i.e. Firefox Incognito Mode) should use the RhinoWeb binding main thread method.


Rhino requires a valid Picovoice AccessKey at initialization. AccessKey acts as your credentials when using Rhino SDKs. You can get your AccessKey for free. Make sure to keep your AccessKey secret. Signup or Login to Picovoice Console to get your AccessKey.


Using yarn:

yarn add @picovoice/rhino-angular @picovoice/web-voice-processor

or using npm:

npm install --save @picovoice/rhino-angular @picovoice/web-voice-processor


There are two methods to initialize Rhino:

Public Directory

NOTE: Due to modern browser limitations of using a file URL, this method does not work if used without hosting a server.

This method fetches the model file from the public directory and feeds it to Rhino. Copy the model file into the public directory:


The same procedure can be used for the Rhino context (.rhn) files.


NOTE: This method works without hosting a server, but increases the size of the model file roughly by 33%.

This method uses a base64 string of the model file and feeds it to Rhino. Use the built-in script pvbase64 to base64 your model file:


The output will be a js file which you can import into any file of your project. For detailed information about pvbase64, run:

npx pvbase64 -h

The same procedure can be used for the Rhino context (.rhn) files.

Rhino Model

Rhino saves and caches your model (.pv) and context (.rhn) files in the IndexedDB to be used by Web Assembly. Use a different customWritePath variable to hold multiple model values and set the forceWrite value to true to force an overwrite of the model file. If the model (.pv) or context (.rhn) files change, version should be incremented to force the cached model to be updated. Either base64 or publicPath must be set to instantiate Rhino. If both are set, Rhino will use the base64 parameter.

// Context (.rhn)
const rhinoContext = {
  // or
  base64: ${CONTEXT_BASE64_STRING},
  // Optionals
  customWritePath: 'custom_context',
  forceWrite: true,
  version: 1,
  sensitivity: 0.5,
// Model (.pv)
const rhinoModel = {
  publicPath: ${MODEL_RELATIVE_PATH},
  // or
  base64: ${MODEL_BASE64_STRING},
  // Optionals
  customWritePath: 'custom_model',
  forceWrite: true,
  version: 1,

Additional engine options are provided via the options parameter. Use endpointDurationSec and requireEndpoint to control the engine's endpointing behavior. An endpoint is a chunk of silence at the end of an utterance that marks the end of spoken command.

// Optional. These are the default values
const options = {
  endpointDurationSec: 1.0,
  requireEndpoint: true,

Initialize Rhino

First subscribe to the events from RhinoService. There are five subscription events:

  • inference$: Returns the inference.
  • contextInfo$: Returns the context info once Rhino has loaded successfully.
  • isLoaded$: Returns true if Rhino has loaded successfully.
  • isListening$: Returns true if WebVoiceProcessor has started successfully and Rhino is listening for an utterance.
  • error$: Returns any errors occurred.
import { Subscription } from "rxjs"
import { RhinoService } from "@picovoice/rhino-angular"
  constructor(private rhinoService: RhinoService) {
    this.contextInfoSubscription = rhinoService.contextInfo$.subscribe(
      contextInfo => {
    this.inferenceSubscription = rhinoService.inference$.subscribe(
      inference => {
    this.isLoadedSubscription = rhinoService.isLoaded$.subscribe(
      isLoaded => {
    this.isListeningSubscription = rhinoService.isListening$.subscribe(
      isListening => {
    this.errorSubscription = rhinoService.error$.subscribe(
      error => {

After setting up the subscriber events, initialize Rhino:

async ngOnInit() {
  await this.rhinoService.init(

Process Audio Frames

The Rhino Angular binding uses WebVoiceProcessor to record audio. To start detecting detecting an inference, run the process function:

await this.rhinoService.process();

The process function initializes WebVoiceProcessor. Rhino will then listen and process frames of microphone audio until it reaches a conclusion, then return the result via the inference$ event. Once a conclusion is reached Rhino will enter a paused state. From the paused state Rhino call process again to detect another inference.


When you are done with Rhino call release. This cleans up all resources used by Rhino and WebVoiceProcessor.

ngOnDestroy() {

If any arguments require changes, call release then init again to initialize Rhino with the new settings.


Create custom contexts using the Picovoice Console. Train and download a Rhino context file (.rhn) for the target platform Web (WASM). This model file can be used directly with publicPath, but, if base64 is preferable, convert the .rhn file to a base64 JavaScript variable using the built-in pvbase64 script:

npx pvbase64 -i ${CONTEXT_FILE}.rhn -o ${CONTEXT_BASE64}.js -n ${CONTEXT_BASE64_VAR_NAME}

Similar to the model file (.pv), context files (.rhn) are saved in IndexedDB to be used by Web Assembly. Either base64 or publicPath must be set for the context to instantiate Rhino. If both are set, Rhino will use the base64 model.

const contextModel = {
  publicPath: "${CONTEXT_RELATIVE_PATH}",
  // or
  base64: "${CONTEXT_BASE64_STRING}",

Switching Languages

In order to make inferences in different language you need to use the corresponding model file (.pv). The model files for all supported languages are available here.


For example usage, refer to our Angular demo application.

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