Porcupine Wake Word
Angular Quick Start

Platforms

• Chrome & Chromium-based browsers
• Edge
• Firefox
• Safari

Requirements

• Picovoice Account and AccessKey
• Node.js 14+
• Angular 13+
• npm

Picovoice Account & AccessKey

Signup or Login to Picovoice Console to get your AccessKey. Make sure to keep your AccessKey secret.

Quick Start

Setup

1. Install Node.js.

2. Install the npm packages:

   • @picovoice/porcupine-angular
   • @picovoice/web-voice-processor

npm install @picovoice/porcupine-angular @picovoice/web-voice-processor

Usage

Put the model file in the project's public directory or generate a base64 model using the build in script:

npx pvbase64 -i ${PORCUPINE_PARAMS_PATH} -o ${OUTPUT_FILE_PATH}

Create a porcupineModel object with either of the methods above:

const PORCUPINE_MODEL_BASE64 = /* Base64 representation of the `.pv` model file*/;

const porcupineModel = {
   publicPath: "${MODEL_RELATIVE_PATH}", // or
   base64: PORCUPINE_MODEL_BASE64
}

Add the PorcupineService to an Angular component. Subscribe to the keywordDetection event for the built-in keywords porcupine and bumblebee:

import { Subscription } from "rxjs"
import { PorcupineService } from "@picovoice/porcupine-angular"

export class VoiceWidget {
  private keywordSubscription: Subscription

  constructor(private porcupineService: PorcupineService) {
     this.keywordSubscription = porcupineService.keywordDetection$.subscribe(
       porcupineDetection => {
          console.log(`Porcupine Detected "${porcupineDetection.label}"`)
       });
     this.isLoadedSubscription = porcupineService.isLoaded$.subscribe(
       isLoaded => {
          console.log(isLoaded);
       });
     this.isListeningSubscription = porcupineService.isListening$.subscribe(
       isListening => {
          console.log(isListening);
       });
     this.errorSubscription = porcupineService.error$.subscribe(
       error => {
          console.error(error);
       });
  }

  async ngOnInit() {
    await this.porcupineService.init(
      ${ACCESS_KEY},
      [BuiltInKeyword.Porcupine],
      porcupineModel,
    )
  }

  ngOnDestroy() {
     this.keywordSubscription.unsubscribe();
     this.isLoadedSubscription.unsubscribe();
     this.isListeningSubscription.unsubscribe();
     this.errorSubscription.unsubscribe();
     this.porcupineService.release();
  }
}

The PorcupineService will take care of microphone access and audio downsampling (via @picovoice/web-voice-processor).

Custom Keywords

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

npx pvbase64 -i ${KEYWORD_FILE}.ppn -o ${KEYWORD_BASE64}.js -n ${KEYWORD_BASE64_VAR_NAME}

Similar to the model file (.pv), keyword files (.ppn) are saved in IndexedDB to be used by Web Assembly. Either base64 or publicPath must be set for each keyword to instantiate Porcupine. If both are set, Porcupine will use the base64 model. An arbitrary label is required to identify the keyword once the detection occurs.

const keywordModel = {
  publicPath: "${KEYWORD_RELATIVE_PATH}",
  // or
  base64: "${KEYWORD_BASE64_STRING}",
  label: "${KEYWORD_LABEL}",
}

Then, initialize an instance of Porcupine:

await this.porcupineService.init(
  "${ACCESS_KEY}",
  [keywordModel],
  porcupineModel,
);

Switching Languages

In order to use Porcupine with other languages, you need to use the corresponding model file (.pv) for the desired language. The model files for all supported languages are available on the Picovoice GitHub repository.

Demo

For the Porcupine Angular SDK, there is an Angular demo project available on the Porcupine GitHub repository.

Setup

Clone the Porcupine repository from GitHub:

git clone --recurse-submodules https://github.com/Picovoice/porcupine.git

Usage

1. Install dependencies and run:

cd porcupine/demo/angular
npm install
npm run start

2. Open http://localhost:4200 to view it in the browser.

Resources