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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### Restrictions\n\nIndexedDB and WebWorkers are required to use `Porcupine Angular`. Browsers without support (i.e. Firefox Incognito Mode) \nshould use the [`PorcupineWeb binding`](https://github.com/Picovoice/porcupine/tree/master/binding/web) main thread method.\n\n## Installation\n\n### Package\n\nUsing `Yarn`:\n\n```console\nyarn add @picovoice/porcupine-angular @picovoice/web-voice-processor\n```\n\nor using `npm`:\n\n```console\nnpm install --save @picovoice/porcupine-angular @picovoice/web-voice-processor\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`,\nrun:\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: ${MODEL_BASE64_STRING},\n\n  // Optional\n  customWritePath: 'custom_model',\n  forceWrite: true,\n  version: 1,\n}\n```\n\n### Initialize Porcupine\n\nFirst subscribe to the events from `PorcupineService`. There are four\nsubscription events:\n\n- `keywordDetection$`: Returns the detected keyword.\n- `isLoaded$`: Returns true if `Porcupine` has loaded successfully.\n- `isListening$`: Returns true if `WebVoiceProcessor` has started successfully.\n- `error$`:  Returns any errors occurred.\n\n```typescript\nimport { Subscription } from \"rxjs\"\nimport { PorcupineService } from \"@picovoice/porcupine-angular\"\n\n...\n\n  constructor(private porcupineService: PorcupineService) {\n    this.keywordSubscription = porcupineService.keywordDetection$.subscribe(\n      porcupineDetection => {\n        console.log(`Porcupine Detected \"${porcupineDetection.label}\"`)\n      });\n    this.isLoadedSubscription = porcupineService.isLoaded$.subscribe(\n      isLoaded => {\n        console.log(isLoaded);\n      });\n    this.isListeningSubscription = porcupineService.isListening$.subscribe(\n      isListening => {\n        console.log(isListening);\n      });\n    this.errorSubscription = porcupineService.error$.subscribe(\n      error => {\n        console.error(error);\n      });\n  }\n```\n\nAfter setting up the subscriber events, initialize `Porcupine`:\n\n```typescript\nimport {BuiltInKeyword} from '@picovoice/porcupine-web';\n\nasync ngOnInit() {\n  await this.porcupineService.init(\n    ${ACCESS_KEY},\n    [BuiltInKeyword.Porcupine],\n    porcupineModel,\n  );\n}\n```\n\n### Process Audio Frames\n\nRun the following to start wake word detection:\n\n```typescript\nawait this.porcupineService.start();\n```\n\nThe results are available on `porcupineService.keywordDetection$` as mentioned above.\n\nTo stop wake word detection run:\n\n```typescript\nawait this.porcupineService.stop();\n```\n\n### Clean Up\n\nClean up used resources with:\n\n```typescript\nngOnDestroy(): void {\n  this.keywordSubscription.unsubscribe();\n  this.isLoadedSubscription.unsubscribe();\n  this.isListeningSubscription.unsubscribe();\n  this.errorSubscription.unsubscribe();\n  this.porcupineService.release();\n}\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 `porcupineService`:\n\n```typescript\nawait this.porcupineService.init(\n  ${ACCESS_KEY},\n  keywordModel,\n  porcupineModel,\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## Demo\n\nFor example usage refer to our [Angular Demo application](https://github.com/Picovoice/porcupine/tree/master/demo/angular).\n","readmeFilename":"README.md"}