Porcupine Wake Word
Web Quick Start

Platforms

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

Requirements

• Picovoice Account and AccessKey
• Node.js 16+
• 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 Web Voice Processor and the porcupine Web package:

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

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 PorcupineWorker instance using the model from public directory:

import { PorcupineWorker } from "@picovoice/porcupine-web";

function keywordDetectionCallback(detection) {
  console.log(`Porcupine detected keyword index: ${detection.label}`);
}

const porcupine = await PorcupineWorker.create(
  "${ACCESS_KEY}",
  PorcupineWeb.BuiltInKeyword.Porcupine,
  keywordDetectionCallback,
  {
    publicPath: "${MODEL_RELATIVE_PATH}"
  }
);

or using the base64 model:

import { PorcupineWorker } from "@picovoice/porcupine-web";

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

function keywordDetectionCallback(detection) {
  console.log(`Porcupine detected ${detection.label}`);
}

const porcupine = await PorcupineWorker.create(
  "${ACCESS_KEY}",
  PorcupineWeb.BuiltInKeyword.Porcupine,
  keywordDetectionCallback,
  {
    base64: PORCUPINE_MODEL_BASE64
  }
)

Subscribe the engine to the Web Voice Processor:

import { WebVoiceProcessor } from "@picovoice/web-voice-processor"

await WebVoiceProcessor.subscribe(porcupine);

Release resources explicitly when done with Porcupine:

await WebVoiceProcessor.unsubscribe(porcupine);
porcupine.release()
porcupine.terminate()

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:

const porcupine = await PorcupineWorker.create(
  "${ACCESS_KEY}",
  [keywordModel],
  keywordDetectionCallback,
  porcupineModel,
  options
);

Non-English Languages

In order to detect non-English wake words you need to use the corresponding model file (.pv). The model files for all supported languages are available on the Picovoice GitHub repository .

Demo

For the Porcupine Web SDK, there is a Web 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 the dependencies and use the start script with a language code to start the demo in the language of your choice (e.g. de -> German, ko -> Korean). To see a list of available languages, run start without a language code.

cd porcupine/demo/web
npm install
npm run start ${LANGUAGE}

2. Open http://localhost:5000 to view it in the browser.

Resources