Porcupine — .NET Quick Start

Requirements

• .NET Core 3.1
• OpenAL

Compatibility

• Linux (x86_64)
• macOS (x86_64)
• Windows (x86_64)

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

Both demos use Microsoft's .NET Core framework.

MicDemo uses OpenAL. On Windows, install using the OpenAL Windows Installer.

On Linux use apt-get

sudo apt-get install libopenal-dev

On Mac use Brew

brew install openal-soft

Once .NET Core and OpenAL have been installed, you can build with the dotnet CLI

dotnet build -c MicDemo.Release
dotnet build -c FileDemo.Release

Usage

NOTE: the working directory for all dotnet commands is:

porcupine/demo/dotnet/PorcupineDemo

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. If a stereo file is provided it only processes the first (left) channel. The following processes a file looking for instances of the phrase "Picovoice":

dotnet run -c FileDemo.Release -- --input_audio_path ${AUDIO_PATH} --keywords picovoice

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

dotnet run -c FileDemo.Release -- --help

To detect multiple phrases concurrently provide them as separate arguments:

dotnet run -c FileDemo.Release -- --input_audio_path ${AUDIO_PATH} --keywords grasshopper porcupine

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

dotnet run -c FileDemo.Release -- --input_audio_path ${AUDIO_PATH} \
--keyword_paths ${KEYWORD_PATH_ONE} ${KEYWORD_PATH_TWO}

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

dotnet run -c FileDemo.Release -- --input_audio_path ${AUDIO_PATH} \
--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

This 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":

dotnet run -c MicDemo.Release -- --keywords picovoice

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

dotnet run -c MicDemo.Release -- --help

To detect multiple phrases concurrently provide them as separate arguments:

dotnet run -c MicDemo.Release -- --keywords picovoice porcupine

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

dotnet run -c MicDemo.Release -- --keyword_paths ${KEYWORD_PATH_ONE} ${KEYWORD_PATH_TWO}

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:

dotnet run -c MicDemo.Release -- --show_audio_devices

It provides information about various audio input devices on the box. On a Windows PC, this is the output:

Available input devices:
 
    Device 0: Microphone Array (Realtek(R) Au
    Device 1: Microphone Headset USB

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

dotnet run -c MicDemo.Release -- --keywords picovoice --audio_device_index 1

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

dotnet run -c MicDemo.Release -- --keywords picovoice --audio_device_index 1 --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.