https://github.com/gabe-zhang/dawg
A voice-controlled smart home assistant
https://github.com/gabe-zhang/dawg
azure iot text2speech
Last synced: 5 months ago
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A voice-controlled smart home assistant
- Host: GitHub
- URL: https://github.com/gabe-zhang/dawg
- Owner: gabe-zhang
- License: mit
- Created: 2024-12-04T04:41:59.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-10T10:28:54.000Z (over 1 year ago)
- Last Synced: 2025-07-31T14:32:50.181Z (12 months ago)
- Topics: azure, iot, text2speech
- Language: Python
- Homepage:
- Size: 1.71 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Dawg: Your AI-Powered Home Buddy
Dawg is a voice-controlled smart home assistant that combines edge and cloud computing to provide real-time environmental monitoring and natural voice interactions. Built on the DE10-Nano platform with Azure cloud services integration.
## Features
- Voice-controlled environmental monitoring
- Real-time sensor data collection (temperature, humidity, brightness)
- Natural language processing for voice commands
- Edge computing capabilities with cloud AI integration
## Project Structure
```
dawg/
├── pyproject.toml
├── README.md
└── src/
├── __init__.py
├── keyword_search.py # Intent classification from voice input
├── main.py
├── sensor/ # Sensor interface package
├── speech2text.py
├── text2speech.py
└── utils.py
```
### Component Description
- `keyword_search.py`: Analyzes transcribed text to detect user intent and categories
- `main.py`: Orchestrates the complete pipeline from audio input to response
- `sensor/`: Package handling RSF2 sensor array interactions
- `speech2text.py`: Handles audio transcription using Azure services
- `text2speech.py`: Converts text responses to speech output
- `utils.py`: Common utilities and helper functions
## Hardware Requirements
- DE10-Nano development board
- RSF2 Sensor Array
- Temperature sensor
- Humidity sensor
- Brightness sensor
- WiFi dongle
- Microphone
- Speaker
## Software
- Python 3.x
## Installation
1\. Clone the repository:
```bash
git clone https://github.com/gabe-zhang/dawg.git
cd dawg
```
2\. Install dependencies:
```bash
pip install --upgrade pip
pip install -e .
```
## Configuration
### 1. Environment Variables
Set up the required Azure credentials in your environment:
```bash
export AZURE_SPEECH_API_KEY=
```
For persistent configuration, add this to your `~/.bashrc` or `~/.zshrc`:
```bash
echo 'export AZURE_SPEECH_API_KEY=' >> ~/.bashrc
source ~/.bashrc
```
### 2. Hardware Setup
Set up the DE10-Nano hardware configuration according to the provided system diagram:
- Connect the RSF2 Sensor Array
- Attach the WiFi dongle
- Connect microphone and speaker to appropriate ports
## Usage
Run the main application with an audio file input:
```bash
python -m src.main audio_input.wav
```
### Voice Commands
The system responds to natural language queries about:
- Temperature readings
- Humidity levels
- Light conditions
- Combined environmental status
Example commands:
- "What's the temperature?"
- "How humid is it?"
- "How bright is the room?"
## System Architecture
The system consists of three main components:
1. **Hardware Components**
- RSF2 Sensor Array for environmental monitoring
- DE10-Nano for local processing
- Audio I/O devices
2. **Edge Processing**
- Analog-to-Digital conversion
- Central Processing Unit
- Script execution
- Command classification
3. **Cloud Services**
- Azure Speech-to-Text
- Azure Text-to-Speech
## Potential Improvements
- Audio kernel installation for on-device speakers and microphones
- Continuous audio interaction support
- Additional sensor integration (camera, accelerometer)
- Enhanced natural language processing capabilities
## Contributors
- [Gabriel Zhang](https://github.com/gabe-zhang)
- Zhenghao Wang