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Inc"},"license":"Apache-2.0","keywords":["porcupine","web","voice","speech","recognition","ai","hotword","wake","word","offline","dom"],"description":"Porcupine wake word engine for web browsers (via WebAssembly)","maintainers":[{"name":"kyeo","email":"kyeo@picovoice.ai"},{"name":"kenarsa","email":"alireza@picovoice.ai"},{"name":"ilavery","email":"ian@picovoice.ai"},{"name":"erismikpico","email":"eric@picovoice.ai"},{"name":"matt200-ok","email":"matthew@picovoice.ai"},{"name":"gabe-picovoice","email":"gabriel@picovoice.ai"}],"readme":"# Porcupine Binding for Web\n\n## Porcupine wake word engine\n\nMade in Vancouver, Canada by [Picovoice](https://picovoice.ai)\n\nPorcupine is a highly accurate and lightweight wake word engine. It enables building always-listening voice-enabled\napplications using cutting edge voice AI.\n\nPorcupine is:\n\n- private and offline\n- [accurate](https://github.com/Picovoice/wake-word-benchmark)\n- [resource efficient](https://www.youtube.com/watch?v=T0tAnh8tUQg) (runs even on microcontrollers)\n- data efficient (wake words can be easily generated by simply typing them, without needing thousands of hours of\n  bespoke audio training data and manual effort)\n- scalable to many simultaneous wake-words / always-on voice commands\n- cross-platform\n\n## Compatibility\n\n- Chrome / Edge\n- Firefox\n- Safari\n\n## Requirements\n\nThe Porcupine Web Binding uses [SharedArrayBuffer](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/SharedArrayBuffer).\n\nInclude the following headers in the response to enable the use of `SharedArrayBuffers`:\n\n```\nCross-Origin-Opener-Policy: same-origin\nCross-Origin-Embedder-Policy: require-corp\n```\n\nRefer to our [Web demo](../../demo/web) for an example on creating a server with the corresponding response headers.\n\nBrowsers that don't support `SharedArrayBuffers` or applications that don't include the required headers will fall back to using standard `ArrayBuffers`. This will disable multithreaded processing.\n\n### Restrictions\n\nIndexedDB is required to use `Porcupine` in a worker thread. Browsers without IndexedDB support\n(i.e. Firefox Incognito Mode) should use `Porcupine` in the main thread.\n\nMulti-threading is only enabled for Porcupine when using on a web worker.\n\n## Installation\n\n### Package\n\nUsing `Yarn`:\n\n```console\nyarn add @picovoice/porcupine-web\n```\n\nor using `npm`:\n\n```console\nnpm install --save @picovoice/porcupine-web\n```\n\n### AccessKey\n\nPorcupine requires a valid Picovoice `AccessKey` at initialization. `AccessKey` acts as your credentials when using\nPorcupine 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\nThere are two methods to pass model files and initialize Porcupine:\n\n### Public Directory\n\n**NOTE**: Due to modern browser limitations of using a file URL, this method does __not__ work if used without hosting a\nserver.\n\nThis method fetches [the model file](https://github.com/Picovoice/porcupine/blob/master/lib/common/porcupine_params.pv)\nfrom the public directory and feeds it to Porcupine.\nCopy the model file into the public directory:\n\n```console\ncp ${PORCUPINE_MODEL_FILE} ${PATH_TO_PUBLIC_DIRECTORY}\n```\n\nThe same procedure can be used for the [custom keyword files](#custom-keywords) (`.ppn`) files.\n\n### Base64\n\n**NOTE**: This method works without hosting a server, but increases the size of the model file roughly by 33%.\n\nThis method uses a base64 string of the model file and feeds it to Porcupine. Use the built-in script `pvbase64` to\nbase64 your model file:\n\n```console\nnpx pvbase64 -i ${MODEL_FILE} -o ${OUTPUT_DIRECTORY}/${MODEL_NAME}.js\n```\n\nThe output will be a js file which you can import into any file of your project. For detailed information\nabout `pvbase64`, run:\n\n```console\nnpx pvbase64 -h\n```\n\nThe same procedure can be used for the [custom keyword files](#custom-keywords) (`.ppn`) files.\n\n### Porcupine Model\n\nPorcupine saves and caches your parameter model file (`.pv`) in IndexedDB to be used by Web Assembly.\nUse a different `customWritePath` variable to hold multiple model values and set the `forceWrite` value to true to force\nre-save the model file.\nIf the model file changes, `version` should be incremented to force the cached models to be updated.\nEither `base64` or `publicPath` must be set to instantiate Porcupine. If both are set, Porcupine will use the `base64`\nmodel.\n\n```typescript\n// Model (.pv)\nconst porcupineModel = {\n  publicPath: ${MODEL_RELATIVE_PATH},\n  // or\n  base64: ${MODEL_BASE64_STRING},\n\n  // Optional\n  customWritePath: 'custom_model',\n  forceWrite: true,\n  version: 1,\n}\n```\n\n### Initialize Porcupine\n\nCreate a `keywordDetectionCallback` function to get the results from the engine:\n\n```typescript\nfunction keywordDetectionCallback(keyword) {\n  console.log(`Porcupine detected keyword: ${keyword.label}`);\n}\n```\n\ncreate an `options` object and add a `processErrorCallback` function if you would like to catch errors:\n\n```typescript\nfunction processErrorCallback(error: string) {\n...\n}\n\noptions.processErrorCallback = processErrorCallback;\n```\n\nInitialize an instance of `Porcupine` in the main thread:\n\n```typescript\nconst handle = await Porcupine.create(\n  ${ACCESS_KEY},\n  PorcupineWeb.BuiltInKeyword.Porcupine,\n  keywordDetectionCallback,\n  porcupineModel,\n  options // optional options\n);\n```\n\nor initialize an instance of `Porcupine` in a worker thread:\n\n```typescript\nconst handle = await PorcupineWorker.create(\n  ${ACCESS_KEY},\n  PorcupineWeb.BuiltInKeyword.Porcupine,\n  keywordDetectionCallback,\n  porcupineModel,\n  options // optional options\n);\n```\n\n### Process Audio Frames\n\nThe result is received from `keywordDetectionCallback` as defined above.\n\n```typescript\nfunction getAudioData(): Int16Array {\n... // function to get audio data\n  return new Int16Array();\n}\n\nfor (; ;) {\n  await handle.process(getAudioData());\n  // break on some condition\n}\n```\n\n### Clean Up\n\nClean up used resources by `Porcupine` or `PorcupineWorker`:\n\n```typescript\nawait handle.release();\n```\n\n### Terminate\n\nTerminate `PorcupineWorker` instance:\n\n```typescript\nawait handle.terminate();\n```\n\n## Custom Keywords\n\nCreate custom keywords using the [Picovoice Console](https://console.picovoice.ai/).\nTrain and download a Porcupine keyword model (`.ppn`) for the target platform `Web (WASM)`. \nThis model file can be used directly with `publicPath`, but, if `base64` is preferable, convert the `.ppn` file to a base64 \nJavaScript variable using the built-in `pvbase64` script:\n\n```console\nnpx pvbase64 -i ${KEYWORD_FILE}.ppn -o ${KEYWORD_BASE64}.js -n ${KEYWORD_BASE64_VAR_NAME}\n```\n\nSimilar to the model file (`.pv`), keyword files (`.ppn`) are saved in IndexedDB to be used by Web Assembly.\nEither `base64` or `publicPath` must be set for each keyword to instantiate Porcupine. \nIf both are set, Porcupine will use the `base64` model. \nAn arbitrary `label` is required to identify the keyword once the detection occurs.\n\n```typescript\n// custom keyword (.ppn)\nconst keywordModel = {\n  publicPath: ${KEYWORD_RELATIVE_PATH},\n  // or\n  base64: ${KEYWORD_BASE64_STRING},\n  label: ${KEYWORD_LABEL},\n  // Optional\n  customWritePath: 'custom_keyword',\n  forceWrite: true,\n  version: 1,\n}\n```\n\nThen, initialize an instance of `Porcupine`:\n\n```typescript\nconst handle = await Porcupine.create(\n  ${ACCESS_KEY},\n  [keywordModel],\n  keywordDetectionCallback,\n  porcupineModel,\n  options\n);\n```\n\n## Non-English Languages\n\nIn order to detect non-English wake words you need to use the corresponding model file (`.pv`). The model files for all\nsupported languages are available [here](https://github.com/Picovoice/porcupine/tree/master/lib/common).\n\n## Train Models over API\n\nYou can train models over API without going to the console:\n\n```javascript\nPorcupine.trainWakeWordFromPhrase(\n  \"${ACCESS_KEY}\",     // AccessKey obtained from Picovoice Console (https://console.picovoice.ai/)\n  \"${WRITE_PATH}\",     // Custom path/key used to store the trained model in IndexedDB\n  \"${LANGUAGE}\",       // Two-character language code\n  \"${PHRASE}\")        // Phrase to create a wake word from\n```\n\nCheck [Porcupine Model API](https://picovoice.ai/docs/model-api/porcupine/) docs for a list of supported languages and platforms.\n\n## Demo\n\nFor example usage refer to our [Web demo application](https://github.com/Picovoice/porcupine/tree/master/demo/web).\n","readmeFilename":"README.md"}