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Porcupine - On-device wake word detection engine powered by deep learning.

  •    C

Try out Porcupine using its interactive web demo. You need a working microphone. Try out Porcupine by downloading it's Android demo application. The demo application allows you to test Porcupine on a variety of wake words in any environment.

project_alias - Alias is a teachable “parasite” that is designed to give users more control over their smart assistants, both when it comes to customisation and privacy

  •    Python

The Alias software can be flashed onto a micro SD card, for a fast and easy setup. Make sure the respeaker hat is attached to the Raspberry Pi. We recommend to use the Easy Setup but if you wish to install the project from scratch use the Manual Install instructions.

wakeword-benchmark - wake word engine benchmark framework

  •    Python

The primary purpose of this benchmark framework is to provide a scientific comparison between different wake-word detection engines in terms of accuracy and runtime metrics. Currently, the framework is configured for Alexa as the test wake-word. But it can be configured for any other wake-words as described here. Common Voice is used as background dataset, i.e., dataset without utterances of the wake-word. It can be downloaded from here. Only recordings with at least two up-votes and no down-votes are used (this reduces the size of the dataset to ~125 hours).






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