# Porcupine Wake Word Engine Made in Vancouver, Canada by [Picovoice](https://picovoice.ai) 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, 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](https://console.picovoice.ai/). ## Compatibility - Rust 1.54+ - Runs on Linux (x86_64), macOS (x86_64 and arm64), Windows (x86_64), Raspberry Pi, NVIDIA Jetson (Nano), and BeagleBone ## Installation First you will need [Rust and Cargo](https://rustup.rs/) installed on your system. To add the porcupine library into your app, add `pv_porcupine` to your apps `Cargo.toml` manifest: ```toml [dependencies] pv_porcupine = "*" ``` If you prefer to clone the repo and use it locally, first run `copy.sh`. (**NOTE:** on Windows, Git Bash or another bash shell is required, or you will have to manually copy the libs into the project). Then you can reference the local binding location: ```toml [dependencies] pv_porcupine = { path = "/path/to/rust/binding" } ``` ## AccessKey Porcupine requires a valid Picovoice `AccessKey` at initialization. `AccessKey` acts as your credentials when using Porcupine SDKs. You can get your `AccessKey` for free. Make sure to keep your `AccessKey` secret. Signup or Login to [Picovoice Console](https://console.picovoice.ai/) to get your `AccessKey`. ## Usage To create an instance of the engine you first create a PorcupineBuilder instance with the configuration parameters for the wake word engine and then make a call to `.init()`: ```rust use porcupine::{BuiltinKeywords, PorcupineBuilder}; let access_key = "${ACCESS_KEY}"; // AccessKey obtained from Picovoice Console (https://console.picovoice.ai/) let porcupine: Porcupine = PorcupineBuilder::new_with_keywords(access_key, &[BuiltinKeywords::Porcupine]).init().expect("Unable to create Porcupine"); ``` In the above example, we've initialized the engine to detect the built-in wake word "Porcupine". Built-in keywords are contained in the package with the `BuiltinKeywords` enum type. Porcupine can detect multiple keywords concurrently: ```rust let porcupine: Porcupine = PorcupineBuilder::new_with_keywords(access_key, &[BuiltinKeywords::Porcupine, BuiltinKeywords::Blueberry, BuiltinKeywords::Bumblebee]) .init().expect("Unable to create Porcupine"); ``` To detect custom keywords, use `PorcupineBuilder`'s `new_with_keyword_paths` method to pass in `*.ppn` file paths instead: ```rust let porcupine: Porcupine = PorcupineBuilder::new_with_keyword_paths(access_key, &["/absolute/path/to/keyword/one.ppn", "/absolute/path/to/keyword/two.ppn"]) .init().expect("Unable to create Porcupine"); ``` The language can be changed by passing in an appropriate `*.pv` file path into the `model_path` method: ```rust let porcupine: Porcupine = PorcupineBuilder::new_with_keyword_paths(access_key, &["/absolute/path/to/keyword/one.ppn"]) .model_path("/path/to/another/language_params.pv") .init().expect("Unable to create Porcupine"); ``` The sensitivity of the engine can be tuned per keyword using the `sensitivities` method: ```rust let porcupine: Porcupine = PorcupineBuilder::new_with_keywords(access_key, &[BuiltinKeywords::Porcupine, BuiltinKeywords::Bumblebee]) .sensitivities(&[0.2f32, 0.42f32]) .init().expect("Unable to create Porcupine"); ``` 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. When initialized, the valid sample rate is given by `sample_rate()`. Expected frame length (number of audio samples in an input array) is given by `frame_length()`. 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. ```rust fn next_audio_frame() -> Vec { // get audio frame } loop { if let Ok(keyword_index) = porcupine.process(&next_audio_frame()) { if keyword_index >= 0 { // wake word detected! } } } ``` ## 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](../../lib/common). ## Demos Check out the Porcupine Rust demos [here](../../demo/rust)