There are 22 repositories under wake-word-detection topic.
A lightweight, simple-to-use, RNN wake word listener
🗣️ A book and repo to get you started programming voice computing applications in Python (10 chapters and 200+ scripts).
A library for real-time voice processing in web browsers
Few-shot Keyword Spotting in Any Language and Multilingual Spoken Word Corpus
wake word engine benchmark framework
Jarvis Home Automation
Classify audio with neural nets on embedded systems like the Raspberry Pi
MicroSpeech Wake Word example on the Raspberry Pi Pico. This is a port of the example on the TensorFlow repository.
Experiments to test different speech recognition systems for SEPIA Framework
Raspberry pi based humanoid robot.
Create modular, cross-browser, web audio pipelines to record and process audio in background threads. Comes with modules for VAD, ASR, resampling and much more...
Twitch Streamer GPT is a NodeJS-based Twitch enhancement tool, offering interactive stream experiences with AI-powered automated responses, voice command activations, and advanced modules. It's easy to set up and suited for users of all tech levels.
Create any wake word, deploy on any device and operating system.
GPT powered personal voice assistant, immitates GLaDOS from Portal.
End-to-End Keyword Spotting (E2E-KWS) using a character level LSTM
Buildings block for voice-enabled applications in the browser
OpenVoiceOS Voice Satellite
Go wrapper for PicoVoice Porcupine wake-word detection engine
Recognition of 38 speech commands in russian. Based on Yandex Cup 2021 ML Challenge: ASR
Build a Wake Word Detection model for Voice Assistant using PyTorch
Hotword Detection (Wake Word Detection) Android library and sample codes
A ChatGPT based Computer Assistant
vosk wake word plugin for mycroft
This model will be able to detect the trigger words.
CrafyWakeWord it's a library focused on AI-based wake word recognition
This project presents Hera, an Operating System level voice recognition package that understands voice commands to perform actions to simplify the user’s workflow. We propose a modernistic way of interacting with Linux systems, where the latency of conventional physical inputs are minimized through the use of natural language speech recognition.
Wake word detection models in pytorch
Experimental support for nyumaya audio recognition on ESP32
Wake-word tools and implementations for S.E.P.I.A.
Light weight UI to interact with Jarvis via API calls
The aim is a home assistant satellite with voice intergration and dashboard also spotify connect and alarm clock
Small footprint, standalone, zero dependency, offline keyword spotting (KWS) CLI tool.