Step 1: Setting Up the LED Matrix
- Connect the matrix module to GPIO pins (SPI recommended: MOSI, CLK, CS).
- Install Python libraries like
luma.led_matrix or max7219 for matrix control.
from luma.led_matrix.device import max7219
from luma.core.interface.serial import spi, noop
serial = spi(port=0, device=0, gpio=noop())
device = max7219(serial, cascaded=1)
device.show_message("HELLO", delay=0.1)
Step 2: Voice Recognition Setup
- Install Python libraries such as
SpeechRecognition and pyaudio.
- Use Google Web Speech API (requires internet) or install
vosk for offline speech recognition.
import speech_recognition as sr
recognizer = sr.Recognizer()
with sr.Microphone() as source:
print("Say something:")
audio = recognizer.listen(source)
command = recognizer.recognize_google(audio)
print("You said:", command)
Step 3: Mapping Voice Commands to LED Actions
- Create a dictionary of common commands like "left", "right", "blink", "clear".
- Use
if-else or match-case statements to match commands and display patterns on the LED matrix.
if "blink" in command:
for _ in range(5):
device.clear()
time.sleep(0.2)
device.show_message("HI")
time.sleep(0.2)
elif "clear" in command:
device.clear()
Project Expansion Ideas:
- Display weather updates using API integration
- Use predefined images or animations with the matrix
- Allow setting custom messages by voice
Troubleshooting Tips:
- Ensure microphone access permissions are correct on Raspberry Pi OS.
- Check pin configurations and power to LED matrix.
- Add print statements to debug recognized commands and hardware responses.
This hands-on project helps reinforce Raspberry Pi GPIO control, Python programming, and speech processing. It sets the foundation for more advanced voice-interactive robotics and IoT systems that respond to human input in real-time.
