rhino

Rhino Speech-to-Intent Engine

Made in Vancouver, Canada by Picovoice

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 would like to order a drink and emits the following inference result:

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

Rhino is:

• using deep neural networks trained in real-world environments.
• compact and computationally-efficient, making it perfect for IoT.
• self-service. Developers and designers can train custom models using Picovoice Console.

Compatibility

• Go 1.16+
• Runs on Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64), Raspberry Pi, NVIDIA Jetson (Nano) and BeagleBone

Installation

go get github.com/Picovoice/rhino/binding/go/v2

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.

Usage

To create an instance of the engine with default parameters, pass an AccessKey and a path to a Rhino context file (.rhn) to the NewRhino function and then make a call to .Init().

import . "github.com/Picovoice/rhino/binding/go"

const accessKey string = "${ACCESS_KEY}" // obtained from Picovoice Console (https://console.picovoice.ai/)

rhino = NewRhino(accessKey, "/path/to/context/file.rhn")
err := rhino.Init()
if err != nil {
    // handle error
}

The context file is a Speech-to-Intent context created either using Picovoice Console or one of the default contexts available on Rhino's GitHub repository.

The sensitivity of the engine can be tuned using the sensitivity parameter. It is a floating-point number within [0, 1]. A higher sensitivity value results in fewer misses at the cost of (potentially) increasing the erroneous inference rate. You can also override the default Rhino model (.pv), which is required when using a non-English context.

To override these parameters, you can create a Rhino struct directly and then call Init():

import . "github.com/Picovoice/rhino/binding/go/v2"

const accessKey string = "${ACCESS_KEY}" // obtained from Picovoice Console (https://console.picovoice.ai/)

rhino := Rhino{
    AccessKey: accessKey,
    ContextPath: "/path/to/context/file.rhn",
    Sensitivity: 0.7,
    ModelPath: "/path/to/rhino/params.pv"}
err := rhino.Init()
if err != nil {
    // handle error
}

Once initialized, you can start passing in frames of audio for processing. The engine accepts 16-bit linearly-encoded PCM and operates on single-channel audio. The sample rate that is required by the engine is given by SampleRate and number of samples-per-frame is FrameLength.

To feed audio into Rhino, use the Process function in your capture loop. You must have called Init() before calling Process.

func getNextFrameAudio() []int16{
    // get audio frame
}

for {
    isFinalized, err := rhino.Process(getNextFrameAudio())
    if isFinalized {
        inference, err := rhino.GetInference()
        if inference.IsUnderstood {
            intent := inference.Intent
            slots := inference.Slots
            // add code to take action based on inferred intent and slot values
        } else {
            // add code to handle unsupported commands
        }
    }
}

When done with the engine, resources have to be released explicitly.

rhino.Delete()

Using a defer call to Delete() after Init() is also a good way to ensure cleanup.

Non-English Contexts

In order to detect non-English contexts you need to use the corresponding model file. The model files for all supported languages are available here.

Demos

Check out the Rhino Go demos here