rustPorcupine — Rust Quick Start

  • End-to-End Voice Platform
  • Offline Voice Recognition
  • Local Speech Recognition
  • Speech-to-Intent
  • Domain-Specific NLU
  • Wake Word Detection
  • Raspberry Pi
  • BeagleBone
  • NVIDIA Jetson
  • Linux
  • macOS
  • Windows
  • Rust

Requirements

  • Rust 1.54+
  • Cargo

Compatibility

  • Linux (x86_64)
  • macOS (x86_64)
  • Windows (x86_64)
  • Raspberry Pi (all variants)
  • NVIDIA Jetson (Nano)
  • BeagleBone

Cloning the Repository

If using SSH, clone the repository with:

git clone [email protected]:Picovoice/porcupine.git

If using HTTPS, then type:

git clone https://github.com/Picovoice/porcupine.git

Installation

The microphone demo uses miniaudio-rs for cross-platform audio capture. It uses bindgen and therefore requires clang to be installed and on the path. Use the Bindgen docs for instructions on how to install clang for various Operating Systems and distros.

Usage

NOTE: The working directory for the following Cargo commands is:

porcupine/demo/rust/filedemo # File Demo
porcupine/demo/rust/micdemo # Microphone Demo

File Demo

The file demo uses Porcupine to scan for keywords in a wave file. The demo is mainly useful for quantitative performance benchmarking against a corpus of audio data. Porcupine processes a 16kHz, single-channel audio stream. The following processes a file looking for instances of the phrase "Picovoice":

cargo run --release -- --input_audio_path "path/to/input.wav" --keywords picovoice

keywords is a shorthand for using built-in keyword files shipped with the package. The list of built-in keyword files can be seen in the usage string:

cargo run --release -- --help

To detect multiple phrases concurrently, provide them as comma-separated values. If the wake word is more than a single word, surround the argument in quotation marks:

cargo run --release -- --input_audio_path "path/to/input.wav" --keywords grasshopper,"hey siri"

To detect custom keywords (e.g. models created using Picovoice Console) use keyword_paths argument:

cargo run --release -- --input_audio_path "path/to/input.wav" \
--keyword_paths "/path/to/keyword/one.ppn,/path/to/keyword/two.ppn"

The sensitivity of the engine can be tuned per keyword using the sensitivities input argument:

cargo run --release -- --input_audio_path "path/to/input.wav" \
--keywords grasshopper,porcupine --sensitivities 0.3,0.6

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.

Microphone Demo

The microphone demo opens an audio stream from a microphone and detects utterances of a given wake word. The following opens the default microphone and detects occurrences of "Picovoice":

cargo run --release -- --keywords picovoice

keywords is a shorthand for using built-in keyword files shipped with the package. The list of built-in keyword files can be seen in the usage string:

cargo run --release -- --help

To detect multiple phrases concurrently provide them as comma-separated values. If the wake word is more than a single word, surround the argument in quotation marks:

cargo run --release -- --keywords grasshopper,"hey siri"

To detect custom keywords (e.g. models created using Picovoice Console) use keyword_paths argument:

cargo run --release -- --keyword_paths "/path/to/keyword/one.ppn","/path/to/keyword/two.ppn"

It is possible that the default audio input device is not the one you wish to use. There are a couple of debugging facilities baked into the demo application to solve this. First, type the following into the console:

cargo run --release -- --show_audio_devices

It provides information about various audio input devices on the box. On a is an example output from a Windows machine:

Capture Devices
0: Microphone Array (Realtek(R) Audio)
1: Microphone (USB Audio Device)

You can use the device index to specify which microphone to use for the demo. For instance, if you want to use the USB microphone in the above example, you can invoke the demo application as below:

cargo run --release -- --keywords picovoice --audio_device_index 1

Exact system setups don't always play well with certain audio backends. If this is the case you can override the default with a specific backend:

cargo run -- --release --keywords picovoice --audio_device_index 1 --audio_backend Alsa

If the problem persists we suggest storing the recorded audio into a file for inspection. This can be achieved with:

cargo run --release -- --keywords picovoice --audio_device_index 1 --audio_backend Alsa --output_path ./test.wav

If after listening to stored file there is no apparent problem detected please open an issue.

Custom Wake Word

You can create custom Porcupine wake word models using Picovoice Console.


Issue with this doc? Please let us know.