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It enables building always-listening voice-enabled\napplications.\n\n> Porcupine wake word models for all major voice assistants (`Alexa`, `Hey Google`, `Ok Google`, and `Hey Siri`) are\n> available for free (under Apache 2.0)\n\nPorcupine is also available for React Native, as a separate package. See [@picovoice/porcupine-react-native](https://www.npmjs.com/package/@picovoice/porcupine-react-native).\n\n## Introduction\n\nThe Porcupine SDK for React is based on the Porcupine SDK for Web. The library provides a React hook: `usePorcupine`. The hook will take care of microphone access and audio downsampling (via `@picovoice/web-voice-processor`) and provide a wake word detection event to which your application can subscribe.\n\n## Compatibility\n\nThe Picovoice SDKs for Web are powered by WebAssembly (WASM), the Web Audio API, and Web Workers.\n\nAll modern browsers (Chrome/Edge/Opera, Firefox, Safari) are supported, including on mobile. Internet Explorer is _not_ supported.\n\nUsing the Web Audio API requires a secure context (HTTPS connection), except for `localhost`, for local development.\n\n## Installation\n\nUse `npm` or `yarn` to install the package and its peer dependencies. Each spoken language (e.g. 'en', 'de') is a separate package. For this example we'll use English:\n\n```console\nyarn add @picovoice/porcupine-web-react @picovoice/porcupine-web-en-worker @picovoice/web-voice-processor`\n```\n\n(or)\n\n```console\nnpm install @picovoice/porcupine-web-react @picovoice/porcupine-web-en-worker @picovoice/web-voice-processor`\n```\n\n\n## AccessKey\n\nPorcupine requires a valid Picovoice `AccessKey` at initialization. `AccessKey` acts as your credentials when using Porcupine SDKs.\nYou can get your `AccessKey` for free. Make sure to keep your `AccessKey` secret.\nSignup or Login to [Picovoice Console](https://console.picovoice.ai/) to get your `AccessKey`.\n\n## Usage\n\nThe `usePorcupine` hook provides a collection of fields and methods shown below. You can pass the `keywordEventHandler` to respond to Porcupine detection events. This example uses the builtin keyword \"Picovoice\" with a sensitivity of 0.65.\n\nMake sure you handle the possibility of errors with the `isError` and `errorMessage` fields. Users may not have a working microphone, and they can always decline (and revoke) permissions; your application code should anticipate these scenarios.\n\n### Static Import\n\nUsing static imports for the `@picovoice/porcupine-web-xx-worker` packages is straightforward, but will impact your initial bundle size with an additional ~2 MB. Depending on your requirements, this may or may not be feasible. If you require a small bundle size, see dynamic importing below.\n\n```javascript\nimport React, { useState } from 'react';\nimport { PorcupineWorkerFactory } from '@picovoice/porcupine-web-en-worker';\nimport { usePorcupine } from '@picovoice/porcupine-web-react';\n\nconst accessKey = // AccessKey obtained from [Picovoice Console](https://console.picovoice.ai/)\nconst keywords = [{ builtin: 'Picovoice', sensitivity: 0.65 }];\n\nfunction VoiceWidget(props) {\n  const keywordEventHandler = keywordLabel => {\n    console.log(`Porcupine detected ${keywordLabel}`);\n  };\n\n  const {\n    isLoaded,\n    isListening,\n    isError,\n    errorMessage,\n    start,\n    pause,\n    setKeywordEventHandler\n  } = usePorcupine(\n    PorcupineWorkerFactory,\n    { accessKey: accessKey, keywords: keywords, start: true },\n    keywordEventHandler,\n  );\n}\n```\n\nThe `keywordEventHandler` will log the keyword detections to the browser's JavaScript console. The detection callback function can be changed using the `setKeywordEventHandler` method.\n\n**Important Note**: Internally, `usePorcupine` performs work asynchronously to initialize, as well as asking for microphone permissions. Not until the asynchronous tasks are done and permission given will Porcupine actually be running. Therefore, it makes sense to use the `isLoaded` state to update your UI to let users know your application is actually ready to process voice (and `isError` in case something went wrong). Otherwise, they may start speaking and their audio data will not be processed, leading to a poor/inconsistent experience.\n\n### Dynamic Import / Code Splitting\n\nIf you are shipping Porcupine for Web and wish to avoid adding its ~2 MB to your application's initial bundle, you can use dynamic imports. These will split off the porcupine-web-xx-worker packages into separate bundles and load them asynchronously. This means we need additional logic.\n\nWe add a `useEffect` hook to kick off the dynamic import. We store the result of the dynamically loaded worker chunk into a `useState` hook. When `usePorcupine` receives a non-null/undefined value for the worker factory, it will start up Porcupine.\n\nSee the [Webpack docs](https://webpack.js.org/guides/code-splitting/) for more information about Code Splitting.\n\n```javascript\nimport { useEffect, useState } from 'react';\nimport { usePorcupine } from '@picovoice/porcupine-web-react';\n\nexport default function VoiceWidget() {\n  const [keywordDetections, setKeywordDetections] = useState([]);\n  const [workerChunk, setWorkerChunk] = useState({ workerFactory: null });\n  const [accessKey] = useState(\n    // AccessKey obtained from [Picovoice Console](https://console.picovoice.ai/)\n  );\n  const [keywords] = useState([\n    { builtin: 'Alexa', sensitivity: 0.7 },\n    'Picovoice',\n  ]);\n\n  useEffect(() => {\n    async function loadPorcupineWorkerChunk() {\n      const ppnWorkerFactory = (\n        await import('@picovoice/porcupine-web-en-worker')\n      ).PorcupineWorkerFactory; // <-- Dynamically import the worker\n      console.log('Porcupine worker chunk is loaded.');\n      return ppnWorkerFactory;\n    }\n\n    if (workerChunk.factory === null) {\n      // <-- We only want to load once!\n      loadPorcupineWorkerChunk().then(ppnWorkerFactory => {\n        setWorkerChunk({ workerFactory: ppnWorkerFactory });\n      });\n    }\n  }, [workerChunk]);\n\n  const keywordEventHandler = porcupineKeywordLabel => {\n    setKeywordDetections(x => [...x, porcupineKeywordLabel]);\n  };\n\n  const {\n    isLoaded,\n    isListening,\n    isError,\n    errorMessage,\n    start,\n    pause,\n    setKeywordEventHandler,\n  } = usePorcupine(\n    workerChunk.workerFactory, // <-- When this is null/undefined, it's ignored. Otherwise, usePorcupine will start.\n    { accessKey: accessKey, keywords: keywords },\n    keywordEventHandler\n  );\n}\n```\n\n### Custom wake words\n\nEach language includes a set of built-in keywords. The quickest way to get started is to use one of those. The builtin keywords are licensed under Apache-2.0 and are completely free to use.\n\nCustom wake words are generated using [Picovoice Console](https://console.picovoice.ai/). They are trained from text using transfer learning into bespoke Porcupine keyword files with a `.ppn` extension. The target platform is WebAssembly (WASM), as that is what backs the React library.\n\nThe `.zip` file contains a `.ppn` file and a `_b64.txt` file which contains the binary model encoded with Base64. Copy the base64 and provide it as an argument to Porcupine as below. You will need to also provide a label so that Porcupine can tell you which keyword occurred (\"Deep Sky Blue\", in this case):\n\n```typescript\nconst DEEP_SKY_BLUE_PPN_64 = /* Base64 representation of deep_sky_blue.ppn */\n...\n  const [keywords] = useState([\n    { base64: DEEP_SKY_BLUE_PPN_64, custom: \"Deep Sky Blue\", sensitivity: 0.7 },\n  ]);\n\n...\n  const {\n    isLoaded,\n    isListening,\n    isError,\n    errorMessage,\n    start,\n    resume,\n    pause,\n  } = usePorcupine(\n    workerChunk.workerFactory, // <-- When this is null/undefined, it's ignored. Otherwise, usePorcupine will start.\n    { accessKey: accessKey, keywords: keywords },\n    keywordEventHandler\n  );\n\n...\n```\n\nYou may wish to store the base64 string in a separate JavaScript file and export it to keep your application code separate.\n","readmeFilename":"README.md"}