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Inc"},"license":"Apache-2.0","keywords":["rhino","web","voice","speech","recognition","ai","offline","dom"],"description":"Rhino Speech-to-Intent 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":"# Rhino Binding for Web\n\n## Rhino Speech-to-Intent engine\n\nMade in Vancouver, Canada by [Picovoice](https://picovoice.ai)\n\nRhino is Picovoice's Speech-to-Intent engine. It directly infers intent from spoken commands within a given context of\ninterest, in real-time. For example, given a spoken command:\n\n> Can I have a small double-shot espresso?\n\nRhino infers that the user would like to order a drink and emits the following inference result:\n\n```json\n{\n  \"isUnderstood\": \"true\",\n  \"intent\": \"orderBeverage\",\n  \"slots\": {\n    \"beverage\": \"espresso\",\n    \"size\": \"small\",\n    \"numberOfShots\": \"2\"\n  }\n}\n```\n\nRhino is:\n\n* using deep neural networks trained in real-world environments.\n* compact and computationally-efficient, making it perfect for IoT.\n* self-service. Developers and designers can train custom models using [Picovoice Console](https://console.picovoice.ai/).\n\n## Compatibility\n\n- Chrome / Edge\n- Firefox\n- Safari\n\n## Requirements\n\nThe Rhino 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 `Rhino` in a worker thread. Browsers without IndexedDB support\n(i.e. Firefox Incognito Mode) should use `Rhino` in the main thread.\n\nMulti-threading is only enabled for Rhino when using on a web worker.\n\n## Installation\n\n### Package\n\nUsing `Yarn`:\n\n```console\nyarn add @picovoice/rhino-web\n```\n\nor using `npm`:\n\n```console\nnpm install --save @picovoice/rhino-web\n```\n\n### AccessKey\n\nRhino requires a valid Picovoice `AccessKey` at initialization. `AccessKey` acts as your credentials when using\nRhino 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 initialize Rhino:\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 server.\n\nThis method fetches [the model file](https://github.com/Picovoice/rhino/blob/master/lib/common/rhino_params.pv) from the public directory and feeds it to Rhino. Copy the model file into the public directory:\n\n```console\ncp ${RHINO_MODEL_FILE} ${PATH_TO_PUBLIC_DIRECTORY}\n```\n\nThe same procedure can be used for the [Rhino context](https://github.com/Picovoice/rhino/tree/master/resources/contexts) (`.rhn`) 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 Rhino. Use the built-in script `pvbase64` to base64 your model file:\n\n```console\nnpx pvbase64 -i ${RHINO_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 about `pvbase64`,\nrun:\n\n```console\nnpx pvbase64 -h\n```\n\nThe same procedure can be used for the [Rhino context](https://github.com/Picovoice/rhino/tree/master/resources/contexts) (`.rhn`) files.\n\n### Rhino Model\n\nRhino saves and caches your model (`.pv`) and context (`.rhn`) files in the 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 an overwrite of the model file.\nIf the model (`.pv`) or context (`.rhn`) files change, `version` should be incremented to force the cached model to be updated. Either `base64` or `publicPath` must be set to instantiate Rhino. If both are set, Rhino will use the `base64` parameter.\n\n```typescript\n// Context (.rhn)\nconst rhinoContext = {\n  publicPath: ${CONTEXT_RELATIVE_PATH},\n  // or\n  base64: ${CONTEXT_BASE64_STRING},\n\n  // Optionals\n  customWritePath: 'custom_context',\n  forceWrite: true,\n  version: 1,\n  sensitivity: 0.5,\n}\n\n// Model (.pv)\nconst rhinoModel = {\n  publicPath: ${MODEL_RELATIVE_PATH},\n  // or\n  base64: ${MODEL_BASE64_STRING},\n\n  // Optionals\n  customWritePath: 'custom_model',\n  forceWrite: true,\n  version: 1,\n}\n```\n\nAdditional engine options are provided via the `options` parameter.\nSet `processErrorCallback` to handle errors if an error occurs while processing audio.\nUse `endpointDurationSec` and `requireEndpoint` to control the engine's endpointing behaviour.\nAn endpoint is a chunk of silence at the end of an utterance that marks the end of spoken command.\n\n```typescript\n// Optional. These are the default values\nconst options = {\n  endpointDurationSec: 1.0,\n  requireEndpoint: true,\n  processErrorCallback: (error) => {},\n}\n```\n\n### Initialize Rhino\n\nCreate a `inferenceCallback` function to get the results from the engine:\n\n```typescript\nfunction inferenceCallback(inference) {\n  if (inference.isFinalized) {\n    if (inference.isUnderstood) {\n      console.log(inference.intent)\n      console.log(inference.slots)\n    }\n  }\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}\noptions.processErrorCallback = processErrorCallback;\n```\n\nInitialize an instance of `Rhino` in the main thread:\n\n```typescript\nconst handle = await Rhino.create(\n  ${ACCESS_KEY},\n  rhinoContext,\n  inferenceCallback,\n  rhinoModel,\n  options // optional options\n);\n```\n\nOr initialize an instance of `Rhino` in a worker thread:\n\n```typescript\nconst handle = await RhinoWorker.create(\n  ${ACCESS_KEY},\n  rhinoContext,\n  inferenceCallback,\n  rhinoModel,\n  options // optional options\n);\n```\n\n### Process Audio Frames\n\nThe result is received from `inferenceCallback` as defined above.\n\n```typescript\nfunction getAudioData(): Int16Array {\n... // function to get audio data\n  return new Int16Array();\n}\nfor (; ;) {\n  await handle.process(getAudioData());\n  // break on some condition\n}\n```\n\n### Clean Up\n\nClean up used resources by `Rhino` or `RhinoWorker`:\n\n```typescript\nawait handle.release();\n```\n\n### Terminate\n\nTerminate `RhinoWorker` instance:\n\n```typescript\nawait handle.terminate();\n```\n\n## Contexts\n\nCreate custom contexts using the [Picovoice Console](https://console.picovoice.ai/).\nTrain and download a Rhino context file (`.rhn`) for the target platform `Web (WASM)`.\nThis model file can be used directly with `publicPath`, but, if `base64` is preferable, convert the `.rhn` file to a\nbase64 JavaScript variable using the built-in `pvbase64` script:\n\n```console\nnpx pvbase64 -i ${CONTEXT_FILE}.rhn -o ${CONTEXT_BASE64}.js -n ${CONTEXT_BASE64_VAR_NAME}\n```\n\nSimilar to the model file (`.pv`), context files (`.rhn`) are saved in IndexedDB to be used by Web Assembly.\nEither `base64` or `publicPath` must be set for the context to instantiate Rhino.\nIf both are set, Rhino will use the `base64` model.\n\n```typescript\nconst contextModel = {\n  publicPath: \"${CONTEXT_RELATIVE_PATH}\",\n  // or\n  base64: \"${CONTEXT_BASE64_STRING}\",\n}\n```\n\n## Switching Languages\n\nIn order to make inferences in different language you need to use the corresponding model file (`.pv`).\nThe model files for all supported languages are available [here](https://github.com/Picovoice/rhino/tree/master/lib/common).\n\n## Train Models over API\n\nYou can train models over API without going to the console:\n\n```javascript\nRhino.trainContextFromDynamicSlots(\n  \"${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  \"${YAML_CONTEXT}\", // RhinoContext object containing a base64 representation of or path to a public binary Rhino context model\n  \"${MODEL}\",        // RhinoModel configuration to be used for training\n  {\n    \"${SLOT_NAME}\": new Set([\"${SLOT1}\", \"${SLOT2}\"])\n  }                 // Additional slot values\n);\n```\n\n(or)\n\n```javascript\nRhino.trainContextFromYaml(\n  \"${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  \"${YAML_CONTENT}\",   // YAML configuration in string\n);\n```\n\n`trainContextFromDynamicSlots` is better suited if you would like the add additional slot values to your current Rhino context.\n\nCheck [Rhino Model API](https://picovoice.ai/docs/model-api/rhino/) docs for a list of supported languages.\n\n## Demo\n\nFor example usage refer to our [Web demo application](https://github.com/Picovoice/rhino/tree/master/demo/web).\n","readmeFilename":"README.md"}