ARM-software/ML-KWS-for-MCU
Keyword spotting on Arm Cortex-M Microcontrollers
This project helps embedded systems engineers and firmware developers implement "keyword spotting" features, like "Hey Google" or "Alexa," on small, low-power microcontrollers. It takes audio input and identifies predefined keywords, outputting a prediction for what word was spoken. This enables voice command interfaces for devices with limited processing power.
1,231 stars. No commits in the last 6 months.
Use this if you are developing firmware for embedded devices and need to add robust, efficient voice command recognition for specific keywords.
Not ideal if you need to recognize a wide vocabulary or implement natural language processing, as this is optimized for small, fixed keyword sets.
Stars
1,231
Forks
427
Language
C
License
Apache-2.0
Category
Last pushed
Apr 10, 2019
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ARM-software/ML-KWS-for-MCU"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
Ant-Brain/EfficientWord-Net
OneShot Learning-based hotword detection.
Tony607/Keras-Trigger-Word
How to do Real Time Trigger Word Detection with Keras | DLology
roman-vygon/triplet_loss_kws
Learning Efficient Representations for Keyword Spotting with Triplet Loss
ardamavi/Vocalization-Sign-Language-iOS
Vocalization sign language iOS App with deep learning using CoreML.
hongfeixue/KWS_pytorch
Keyword spotting, Speech wake_up, by pytorch, DNN, CNN, TDNN, DFSMN, LSTM