rustPicovoice Platform — 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 --recurse-submodules [email protected]:Picovoice/picovoice.git

If using HTTPS, then type:

git clone --recurse-submodules https://github.com/Picovoice/picovoice.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:

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

File Demo

The file demo allows testing Picovoice on a corpus of audio files. The demo is mainly useful for quantitative performance benchmarking. The following processes a file looking for instances of the wake phrase defined in the file passed to the --keyword_path argument and then infers the follow-on spoken command using the context defined by the file passed to the --context_path argument:

cargo run --release -- \
--input_audio_path "path/to/input.wav" \
--keyword_path "/path/to/keyword.ppn" \
--context_path "/path/to/context.rhn"

To see all available arguments, use the --help flag:

cargo run --release -- --help

Microphone Demo

The microphone demo opens an audio stream from a microphone and detects utterances of a give wake word(s). The following processes incoming audio from the microphone for instances of the wake phrase defined in the file passed to the --keyword_path argument and then infers the follow-on spoken command using the context defined by the file passed to the --context_path argument. Upon completion of the spoken command inference it resumes wake word detection:

cargo run --release -- \
--keyword_path "/path/to/keyword.ppn" \
--context_path "/path/to/context.rhn"

To see all available arguments, use the -h flag:

cargo run --release -- --help

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 -- \
--keyword_path "/path/to/keyword.ppn" \
--context_path "/path/to/context.rhn" \
--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 -- \
--keyword_path "/path/to/keyword.ppn" \
--context_path "/path/to/context/one.rhn" \
--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 \
--context_path "/path/to/context.rhn" \
--keyword_path "/path/to/keyword.ppn" \
--audio_device_index 1 \
--output_path ./test.wav

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

Create Custom Wake Words & Contexts

You can create custom Porcupine wake word and Rhino context models using Picovoice Console


Issue with this doc? Please let us know.