Rhino NodeJS Demos

This package provides two demonstration command-line applications for Rhino: a file based demo, which scans a compatible WAV file, and a microphone demo.

Introduction to Rhino

Rhino is Picovoice's Speech-to-Intent engine. It directly infers intent from spoken commands within a given context of interest, in real-time. For example, given a spoken command

Can I have a small double-shot espresso?

Rhino infers that the user wants to order a drink and emits the following inference result:

{
  "isUnderstood": "true",
  "intent": "orderBeverage",
  "slots": {
    "beverage": "espresso",
    "size": "small",
    "numberOfShots": "2"
  }
}

Unlike typical NLU inference software, Rhino does not use generic Speech-to-Text transcription, and instead operates on a compact, bespoke model generated for a specific use case; e.g. a coffee maker, or smart home lighting. Unless you deliberately program it to do so, it won't understand phrases like "tell me a joke". Using this approach (combined with Picovoice's proprietary deep learning technology) allows for:

• dramatically improved efficiency (it can even run on tiny microcontrollers)
• accuracy gains from not having to anticipate every possible spoken phrase
• avoiding transcription errors compounding into the intent understanding (e.g. homonyms are much less of an issue, because we probably know which word makes sense).

To learn more about Rhino, see the product, documentation, and GitHub pages.

Compatibility

These demos run Rhino on NodeJS 16+ on the following platforms:

• Windows (x86_64)
• Linux (x86_64)
• macOS (x86_64, arm64)
• Raspberry Pi (3, 4, 5)

Web Browsers

These demos and the bindings upon which they are built are for NodeJS and do not work in a browser. Looking to run Rhino in-browser? There are npm packages available for Web, and dedicated packages for Angular, React, and Vue.

AccessKey

Rhino requires a valid Picovoice AccessKey at initialization. AccessKey acts as your credentials when using Rhino SDKs. You can get your AccessKey for free. Make sure to keep your AccessKey secret. Signup or Login to Picovoice Console to get your AccessKey.

Install NPM package

To install the demos and make them available on the command line, use either of the following yarn or npm commands:

yarn global add @picovoice/rhino-node-demo

(or)

npm install -g @picovoice/rhino-node-demo

Run the mic demo

Using the 'global' install methods above should add rhn-mic-demo to your system path, which we can use to run the mic demo.

Select an input audio device to start recording audio:

rhn-mic-demo --show_audio_devices

This command prints a list of the available devices and its inputs:

index: 0, device name: USB Audio Device
index: 1, device name: MacBook Air Microphone

Specify the input audio device with --audio_device_index and the Speech-to-Intent context (.rhn file) with --context and provide your Picovoice AccessKey with --access_key.

Here is an example using USB Audio Device and commands from the "Smart Lighting" demo from the Rhino GitHub repository (note that context files are platform-dependent; choose the appropriate one for the platform you are using; this demo uses the "mac" version)

rhn-mic-demo --access_key ${ACCESS_KEY} --context ./smart_lighting_mac.rhn --audio_device_index 0

The context source in YAML format will be output to show you the grammar and options that the context supports. The demo will listen for a phrase that the contexts understands, and upon reaching a conclusion (or timeout), it will output the results.

Using device: USB Audio Device
Context info:
-------------
context:
  expressions:
    changeColor:
      - (please) [change, set, switch] (the) $location:location (to) $color:color
      - (please) [change, set, switch] (the) $location:location color (to) $color:color
      - (please) [change, set, switch] (the) $location:location lights (to) $color:color
      ... (etc.) ...

Listening for speech within the context of 'smart_lighting_mac'. Please speak your phrase into the microphone.

# (say e.g. "please turn on the lights in the kitchen")

...

Inference result:
{
    "isUnderstood": true,
    "intent": "changeLightState",
    "slots": {
        "state": "on",
        "location": "kitchen"
    }
}

Try running the mic demo again, but this time say something that it is not designed to understand, like "tell me a joke":

rhn-mic-demo access_key ${ACCESS_KEY} --context_path ../../resources/contexts/mac/smart_lighting_mac.rhn  --audio_device_index 0

...

Using device: sof-hda-dsp Digital Microphone
Listening for speech within the context of 'smart_lighting_mac'. Please speak your phrase into the microphone.

# (say e.g. "tell me a joke")

Inference result:
{
    "isUnderstood": false
}

Run the file demo

The file-based demo allows you to scan a compatible wave file with Rhino. Note: The demo requires 16KHz, 16-bit linear PCM, single-channel (mono) WAV files.

To run the file-based demo, we need to provide a Speech-to-Intent context along with a path to a compatible WAV file.

We can use a couple of test WAV files that are bundled in the Rhino GitHub repository. These are intended to be used with the sample "Coffee Maker" context, also available in the Rhino GitHub repository (note that context files are platform-dependent; choose the appropriate one for the platform you are using; this demo uses the "mac" version)

Run the file demo, and the successful inference with the intent "orderDrink" along with the specific details are returned:

rhn-file-demo \
access_key ${ACCESS_KEY} \
--context_path ../../resources/contexts/mac/coffee_maker_mac.rhn \
--input_audio_file_path ../../resources/audio_samples/test_within_context.wav

...

Inference result of 'test_within_context.wav' using context 'coffee':
{
    "isUnderstood": true,
    "intent": "orderDrink",
    "slots": {
        "size": "medium",
        "numberOfShots": "double shot",
        "coffeeDrink": "americano",
        "milkAmount": "lots of milk",
        "sugarAmount": "some sugar"
    }
}

Trying the file demo on a phrase that the coffee context is not designed to understand (again a sample WAV file from the Rhino GitHub repository):

rhn-file-demo \
access_key ${ACCESS_KEY} \
--context_path ../../resources/contexts/mac/coffee_maker_mac.rhn \
--input_audio_file_path ../../resources/audio_samples/test_out_of_context.wav

...

Inference result of 'test_out_of_context.wav' using context 'coffee':
{
    "isUnderstood": false
}

Common Demo Options

The microphone and file demos both have additional options.

To see the full set of options, use --help:

rhn-mic-demo --help

rhn-file-demo --help

Usage: rhn-mic-demo [options]

Options:
  -c, --context_path <string>       absolute path to rhino context (.rhn extension)
  -a, --access_key <string>         AccessKey obtain from the Picovoice Console (https://console.picovoice.ai/)
  -l, --library_file_path <string>  absolute path to rhino dynamic library
  -m, --model_file_path <string>    absolute path to rhino model
  -s, --sensitivity <number>        sensitivity value between 0 and 1 (default: 0.5)
  -h, --help                        display help for command

Sensitivity

The sensitivity is a floating-point value in the range [0,1] which specifies the tradeoff between miss rate and false alarm. The demo defaults to 0.5. You can override this with --sensitivity:

rhn-mic-demo --context_path ../../resources/contexts/mac/coffee_maker_mac.rhn --sensitivity 0.65

Creating a custom Speech-to-Intent context

To design Speech-to-Intent contexts and train them into RHN files, see the Picovoice Console.

Files generated with the Picovoice Console carry restrictions including (but not limited to): training allowance, time limits, available platforms, and commercial usage.

Custom library and model files

You may override the Rhino model and dynamic libraries by specifying their absolute paths with --model_file_path and --library_file_path, respectively. As with context files, the dynamic library is specific to the platform.

e.g. for macOS (x86_64):

rhn-file-demo \
--access_key ${ACCESS_KEY} \
--input_audio_file_path ../../resources/audio_samples/test_out_of_context.wav \
--context_path ../../resources/contexts/mac/coffee_maker_mac.rhn \
--library_file_path ../../lib/mac/x86_64/libpv_rhino.dylib \
--model_file_path ../../lib/common/rhino_params.pv

Running the demos from the GitHub repository

Use one of yarn or npm to install the package dependencies from the demo/nodejs folder:

cd demo/nodejs
yarn

(or)

cd demo/nodejs
npm install

Microphone demo

Use yarn mic (or npm run mic) to run the mic demo from the demos/nodejs directory. For npm run, note the extra -- needed before specifying commands. This is to disambiguate whether the options are intended for npm or for the demo script. As before, pick a context that matches the platform you are using (these examples use 'mac'):

yarn mic --access_key ${ACCESS_KEY} --context_path ../../resources/contexts/mac/coffee_maker_mac.rhn

(or)

npm run mic -- --access_key ${ACCESS_KEY} --context_path ../../resources/contexts/mac/coffee_maker_mac.rhn

File demo

Use yarn file or npm run file from the demos/nodejs directory. For npm run, note the extra -- needed before specifying commands. This is to disambiguate whether the options are intended for npm itself, or for the demo script.

yarn file \
--access_key ${ACCESS_KEY} \
--input_audio_file_path ../../resources/audio_samples/test_within_context.wav \
--context_path ../../resources/contexts/mac/coffee_maker_mac.rhn

(or)

npm run file -- \
--access_key ${ACCESS_KEY} \
--input_audio_file_path ../../resources/audio_samples/test_within_context.wav \
--context_path ../../resources/contexts/mac/coffee_maker_mac.rhn