# π€Voice-Controlled Light with Malagasy Commands & TinyML
**Control lights using voice commands in Malagasy**, a TinyML project deployed on Arduino Nano 33 BLE Sense.
*"Mirehitra" (Light On) | "Maty" (Light Off)*
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## π Project Overview
This project demonstrates how to train a **Convolutional Neural Network (CNN)** to recognize Malagasy voice commands and deploy it on a microcontroller using **TensorFlow Lite Micro**. The AI model processes audio signals to control a light bulb via Malagasy keywords, bridging language gaps in voice technology.
**Key Features**:
- π£οΈ Supports **Malagasy language** (under-resourced in voice tech).
- π Runs on a **coin-cell battery** with Arduino Nano 33 BLE Sense.
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## π οΈ Hardware & Software
**Hardware**:
- Arduino Nano 33 BLE Sense Rev2 (with built-in microphone).
- Light bulb
- Relay module
- 5V-6V battery
**Software**:
- Google Colab (GPU for training)
- TensorFlow
- Arduino IDE
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## π Project Structure
```bash
βββ Training/
β βββ train_voice_control_model_with_malagasy_words.ipynb # Model training & quantization
βββ voice_command_based_on_TinyML/
βββ voice_command_based_on_TinyML.ino # Arduino deployment code
βββ arduino_audio_provider.cpp
βββ arduino_command_responder.cpp
βββ arduino_main.cpp
βββ audio_provider.h
βββ command_responder.h
βββ feature_provider.cpp
βββ feature_provider.h
βββ main_functions.h
βββ micro_features_micro_features_generator.cpp
βββ micro_features_micro_features_generator.h
βββ micro_features_micro_model_settings.cpp
βββ micro_features_micro_model_settings.h
βββ micro_features_model.cpp
βββ micro_features_model.h
βββ recognize_commands.cpp
βββ recognize_commands.h