Projects/IoT & Electronics/Using TensorFlowJS (Machine Le...
April 14, 2019
2 min read
IoT & Electronics
Using TensorFlowJS (Machine Learning) for Speech Recognition on ESP8266
📺 Watch the Video View on YouTube --- Use TensorFlowJS via WebAudio API and WebGL GPU acceleration on Browser to recognize "keywords". In our case, w...
📺 Watch the Video
Use TensorFlowJS via WebAudio API and WebGL GPU acceleration on Browser to recognize "keywords". In our case, without retraining "UP" turns on LED and "DOWN" turns it off.
FFT on ESP32
📺 Watch the Video
GitHub: debsahu/SpeechRecognitionTensorFlowJS
Speech Recognition on Browser, AsyncWebServer served on ESP8266 to control LED_BUILTIN/GPIO16
- •Uses WebAudio API and WebGL GPU acceleration = speech recognition is done on the browser
- •
http://requests for microphone is blocked for chrome, use firefox instead - •tf.min.js and speech-commands.min.js served from SPIFFs (1MB Program/3MB SPIFFs partition needed)
- •
/uploadand/updateis a morden world's take on updates to ESP8266 - •Uses HTML templates to report LED_BUILTIN/GPIO16 status
- •Speech recognition: "UP" = ON and "DOWN" = OFF, "RIGHT" and "LEFT" ignored
Arduino Libraries needed
platformio.ini is included, use PlatformIO and it will take care of installing the following libraries.
| Library | Link |
|---|---|
| ESPAsyncTCP | https://github.com/me-no-dev/ESPAsyncTCP |
| ESPAsyncWiFiManager | https://github.com/alanswx/ESPAsyncWiFiManager |
| ESP Async WebServer | https://github.com/me-no-dev/ESPAsyncWebServer |
Credits
- •Inspiration(and major code with regards to JS): Rubik's Code
- •TensorFlowJS Documentation: Speech recognition
- •@RuiSantosdotme for HTML Templates