Tag Archives: Speech to Text

Hey everyone, welcome back to the AI on the Edge series!

In today’s lesson, we’re taking another big step forward in building truly interactive AI projects that run right on our Raspberry Pi 5. We’re going to give our hardware a voice — literally. You’ll learn how to control the brightness of an LED using simple voice commands like “low”, “medium”, “high”, “on”, and “off”.

This lesson builds directly on the speech-to-text skills we learned earlier. Using the Fusion Hat’s microphone and the excellent STT library, we create a system where you can speak naturally to your Pi and it responds instantly by changing the LED brightness. We also bring in Python threading so the voice listening doesn’t block the main program — which is a critical skill as our projects get more complex.

One of the things I really like about this project is how it shows the power of combining AI with real hardware. You’re not just making the LED turn on and off anymore — you’re giving it smooth, adjustable brightness control using nothing but your voice. It’s a perfect example of the kind of interactive, intelligent edge computing we’re working toward in this class.

By the end of this lesson, you’ll have a solid understanding of how to use voice commands to control hardware, how to manage multiple things happening at the same time with threading, and how to create a much more natural and user-friendly interface for your projects.

This is the kind of thing that makes your Raspberry Pi projects feel alive and responsive. Whether you eventually want to control motors, lights, robots, or entire systems with your voice, the techniques you learn in this lesson will serve as a strong foundation.

So grab your SunFounder Fusion AI Hat, hook up that red LED, and let’s get your Raspberry Pi listening and responding to your voice commands like a proper smart device!

As always, I encourage you to type the code along with me in the video, then play around with it. Try adding more commands, change the LED color, or combine it with other sensors. That’s where the real learning and creativity happens.

I’m really excited to see what you build with this one!

This is the schematic we are using, from LESSON #5.

Fusion Hat Circuit Diagram — This is the circuit we will use moving forward in the class

In the video, this is the code we developed:

from fusion_hat.pwm import PWM
from fusion_hat.stt import STT
import threading
from queue import Queue
from time import sleep

redPin = 5
redLED = PWM(redPin)
redLED.freq(1000)

stt = STT(language ="en-us")

brightness = "off"
bNumb = 0
running = True
brightQ = Queue()
def blinkBright():
    print("Input Thread is Running")
    global running
    while running:
        print("What Brightness: (off, low, medium, high, on or quit: )")
        cmd = stt.listen(stream = False)
        cmd = cmd.strip()
        print(cmd)
        if cmd == "quit":
            running = False
            break
        brightQ.put(cmd)
    print("Thread is Terminated")
brightThread = threading.Thread(target = blinkBright, daemon = True)
brightThread.start()
print("Main Program Has Started")
try:
    while running:
        if brightQ.empty() == False:
            brightness = brightQ.get()
            if brightness == "quit":
                break
        if brightness == "off":
            bNumb = 0
        if brightness == "low" or brightness == "whoa":
            bNumb = 8
        if brightness == "medium":
            bNumb = 25
        if brightness == "high" or brightness == "hi":
            bNumb = 60
        if brightness == "on":
            bNumb = 100
        redLED.pulse_width_percent(bNumb)
    redLED.pulse_width_percent(0)
    redLED.enable(False)
    print("LED Released")
    print("Program is Terminated")
        
except KeyboardInterrupt:
    running = False
    redLED.pulse_width_percent(0)
    redLED.enable(False)
    print("LED Released")
    print("Program Terminated")

from fusion_hat.pwm import PWM

from fusion_hat.stt import STT

import threading

from queue import Queue

from time import sleep

redPin = 5

redLED = PWM(redPin)

redLED.freq(1000)

stt = STT(language ="en-us")

brightness = "off"

bNumb = 0

running = True

brightQ = Queue()

def blinkBright():

print("Input Thread is Running")

global running

while running:

print("What Brightness: (off, low, medium, high, on or quit: )")

cmd = stt.listen(stream = False)

cmd = cmd.strip()

print(cmd)

if cmd == "quit":

running = False

break

brightQ.put(cmd)

print("Thread is Terminated")

brightThread = threading.Thread(target = blinkBright, daemon = True)

brightThread.start()

print("Main Program Has Started")

try:

while running:

if brightQ.empty() == False:

brightness = brightQ.get()

if brightness == "quit":

break

if brightness == "off":

bNumb = 0

if brightness == "low" or brightness == "whoa":

bNumb = 8

if brightness == "medium":

bNumb = 25

if brightness == "high" or brightness == "hi":

bNumb = 60

if brightness == "on":

bNumb = 100

redLED.pulse_width_percent(bNumb)

redLED.pulse_width_percent(0)

redLED.enable(False)

print("LED Released")

print("Program is Terminated")

except KeyboardInterrupt:

running = False

redLED.pulse_width_percent(0)

redLED.enable(False)

print("LED Released")

print("Program Terminated")

AI On the Edge, Tutorial

AI on the Edge LESSON 11: Control LED on Raspberry Pi With Voice Commands

May 1, 2026 admin

In today’s lesson, we’re taking our first exciting step into giving our Raspberry Pi the ability to understand and respond to our voice. That’s right — we’re going to control a physical LED using nothing but spoken commands! This is a huge milestone in the class because it marks the beginning of building truly interactive AI projects that can listen to us and take action in the real world.

Using the SunFounder Fusion AI Hat’s built-in microphone and the excellent STT (Speech-to-Text) library, we create a simple but powerful voice assistant that can turn an LED on and off with commands like “on”, “off”, and “quit”. I walk you through every single line of the code so you can clearly see how we capture voice input, process the command, and control real hardware.

This lesson is intentionally straightforward because I want you to build a strong foundation. Once you understand how to take a voice command and turn it into physical action, we can start adding more complexity — like controlling multiple devices, adjusting brightness, or even combining voice control with computer vision in future lessons.

One of the things I love most about this project is how it makes the Raspberry Pi feel “alive.” Instead of clicking buttons or typing commands, you can now talk directly to your project. This is the kind of interaction that makes edge AI projects so much fun and so powerful.

By the end of this lesson, you’ll have a working voice-controlled LED and the confidence to start expanding your voice control skills. This is exactly the kind of capability we need as we move forward in the AI on the Edge journey — giving our intelligent systems natural, human-friendly ways to interact with us.

So grab your Fusion AI Hat, hook up that LED, and let’s turn your Raspberry Pi into a voice-controlled device! As always, I strongly encourage you to code along with me in the video and then play around with the program. Try adding more commands, control multiple LEDs, or even have it say something back to you.

This is where things start getting really fun. Let’s get that LED responding to your voice!

This is the schematic of the circuit we are using for our AI class. We go into great detail on this schematic in LESSON #5 if you want to learn more about it.

Now this is the code we developed in this lesson:

from fusion_hat.stt import STT
from fusion_hat.pin import Pin, Mode
from time import sleep

redPin = 17
redLED = Pin(redPin,mode=Mode.OUT)
stt = STT(language="en-us")
while True:
    print("Voice Assistant At the READY!, Speak at Any Time: ")
    command = stt.listen(stream=False)
    command = command.strip()
    print(command)
    if command == "on":
        redLED.high()
        print("LED ON")
    if command == "off":
        redLED.low()
        print("LED OFF")
    if command == "quit":
        break
redLED.low()

from fusion_hat.stt import STT

from fusion_hat.pin import Pin, Mode

from time import sleep

redPin = 17

redLED = Pin(redPin,mode=Mode.OUT)

stt = STT(language="en-us")

while True:

print("Voice Assistant At the READY!, Speak at Any Time: ")

command = stt.listen(stream=False)

command = command.strip()

print(command)

if command == "on":

redLED.high()

print("LED ON")

if command == "off":

redLED.low()

print("LED OFF")

if command == "quit":

break

redLED.low()

AI On the Edge, Tutorial

AI on the Edge LESSON 10: Make Your Raspberry Pi Listen to You with Voice Commands

April 29, 2026 admin

In this video lesson you will learn how to train the Raspberry Pi to take voice commands from you. We do this through the Fusion AI+ hat’s microphone, and a Speech to Text (STT) model. Our goal is to develop the ability to interact with our projects through spoken words. We give commands to the project, and then it responds intelligently with words.

Remember these lessons depend on you using the AI Educational OS, a special version of bookworm that has all the libraries, modules, and models already installed for you. See LESSON #2 in this class for instructions on flashing that OS.

Below is the simple demonstration code we developed to give simple voice commands:

from fusion_hat.stt import STT

stt = STT(language="en-us")

while True:
    print("Say Something: ")
    command = stt.listen(stream=False)
    print(command)

from fusion_hat.stt import STT

stt = STT(language="en-us")

while True:

print("Say Something: ")

command = stt.listen(stream=False)

print(command)

Similar to our Speech to Text example, the first time you run this program you will get a permissions error. You need to open a terminal, and put these commands in one at a time to enable permissions. This only has to be done once, and after that this and all STT programs should run properly.

sudo mkdir -p /opt/vosk_models
sudo chown -R pi:pi /opt/vosk_models
sudo chmod -R 755 /opt/vosk_models

sudo mkdir -p /opt/vosk_models

sudo chown -R pi:pi /opt/vosk_models

sudo chmod -R 755 /opt/vosk_models

Technology Tutorials

Tag Archives: Speech to Text

AI on the Edge LESSON 13: Control LED Brightness with Voice Commands on Raspberry Pi 5

AI on the Edge LESSON 11: Control LED on Raspberry Pi With Voice Commands

AI on the Edge LESSON 10: Make Your Raspberry Pi Listen to You with Voice Commands

Making The World a Better Place One High Tech Project at a Time. Enjoy!