Displaying 1 to 3 from 3 results

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.

mycroft-precise - A lightweight, simple-to-use, RNN wake word listener

  •    Python

A lightweight, simple-to-use, RNN wake word listener. Precise is a wake word listener. Like its name suggests, a wake word listener's job is to continually listen to sounds and speech around the device, and activate when the sounds or speech match a wake word. Unlike other machine learning hotword detection tools, Mycroft Precise is fully open source. Take a look at a comparison here.

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).