porcupine-pertev-wakeword/binding/go

Porcupine Binding for Go

Porcupine Wake Word Engine

Made in Vancouver, Canada by Picovoice

Porcupine is a highly-accurate and lightweight wake word engine. It enables building always-listening voice-enabled applications. It is

• using deep neural networks trained in real-world environments.
• compact and computationally-efficient. It is perfect for IoT.
• cross-platform:
  • Arm Cortex-M, STM32, PSoC, Arduino, and i.MX RT
  • Raspberry Pi, NVIDIA Jetson Nano, and BeagleBone
  • Android and iOS
  • Chrome, Safari, Firefox, and Edge
  • Linux (x86_64), macOS (x86_64, arm64), and Windows (x86_64)
• scalable. It can detect multiple always-listening voice commands with no added runtime footprint.
• self-service. Developers can train custom wake word 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/porcupine/binding/go

AccessKey

Porcupine requires a valid Picovoice AccessKey at initialization. AccessKeys act as your credentials when using Porcupine SDKs. You can create your AccessKey for free. Make sure to keep your AccessKey secret.

To obtain your AccessKey:

1. Login or Signup for a free account on the Picovoice Console.
2. Once logged in, go to the AccessKey tab to create one or use an existing AccessKey.

Usage

To create an instance of the engine you first create a Porcupine struct with the configuration parameters for the wake word engine and then make a call to .Init():

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

porcupine := Porcupine{
    AccessKey: "${ACCESS_KEY}", // AccessKey obtained from Picovoice Console (https://picovoice.ai/console/)
    BuiltInKeywords: []BuiltInKeyword{PICOVOICE}}
err := porcupine.Init()
if err != nil {
    // handle init fail
}

In the above example, we've initialized the engine to detect the built-in wake word "Picovoice". Built-in keywords are constants in the package with the BuiltInKeyword type.

Porcupine can detect multiple keywords concurrently:

porcupine := Porcupine{
    AccessKey: "${ACCESS_KEY}", // AccessKey obtained from Picovoice Console (https://picovoice.ai/console/)
    BuiltInKeywords: []BuiltInKeyword{PICOVOICE, BUMBLEBEE}}
err := porcupine.Init()

To detect non-default keywords, use KeywordPaths parameter instead:

porcupine := Porcupine{
    AccessKey: "${ACCESS_KEY}", // AccessKey obtained from Picovoice Console (https://picovoice.ai/console/)
    KeywordPaths: []string{"/path/to/keyword.ppn"}}
err := porcupine.Init()

In addition to custom keywords, you can override the default Porcupine english model file and/or keyword sensitivities.

Sensitivity is the parameter that enables trading miss rate for the false alarm rate. It is a floating-point number within [0, 1]. A higher sensitivity reduces the miss rate at the cost of increased false alarm rate.

The model file contains the parameters for the wake word engine. To change the language that Porcupine understands, you'll pass in a different model file.

porcupine := Porcupine{
    AccessKey: "${ACCESS_KEY}", // AccessKey obtained from Picovoice Console (https://picovoice.ai/console/)
    BuiltInKeywords: []BuiltInKeyword{PICOVOICE, BUMBLEBEE},
    Sensitivities: []float32{0.4, 0.9},
    ModelPath: "/path/to/model.pv"}
err := porcupine.Init()

When initialized, the valid sample rate is given by SampleRate. Expected frame length (number of audio samples in an input array) is given by FrameLength. The engine accepts 16-bit linearly-encoded PCM and operates on single-channel audio.

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

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

for {
    keywordIndex, err := porcupine.Process(getNextFrameAudio())
    if keywordIndex >= 0 {
        // wake word detected!
    }
}

When done resources have to be released explicitly.

porcupine.Delete()

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

Non-English Wake Words

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

Demos

Check out the Porcupine Go demos here