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How do i achieve a fully functional voice-controlled system with reliable command recognition and LED control?
Am done with my project on developing a home automation voice-controlled system using `MicroPython` and `TinyML` on an `ESP32` microcontroller to recognize specific voice commands (“turn on” and “turn off”) for controlling an LED. It runs smoothly as intended with no errors but sometimes doesn’t respond to the voice command, how can i achieve consistent voice recognition and `LED` control with the `ESP32`, leveraging TinyML and MicroPython.
“`python
from machine import Pin, I2S
import time
import ustruct
import array
import tensorflow as tf
led = Pin(2, Pin.OUT)
i2s = I2S(0,
sck=Pin(14),
ws=Pin(15),
sd=Pin(32),
mode=I2S.RX,
bits=16,
format=I2S.MONO,
rate=16000,
ibuf=2000)
model = tf.lite.Interpreter(model_path=”model.tflite”)
model.allocate_tensors()
input_details = model.get_input_details()
output_details = model.get_output_details()
def read_audio():
audio_data = array.array(‘h’, i2s.read(1024))
audio_samples = ustruct.unpack(‘<1024h', audio_data)
return audio_samples
def final_process_audio():
audio_samples = read_audio()
audio_input = tf.convert_to_tensor(audio_samples, dtype=tf.float32)
audio_input = tf.expand_dims(audio_input, axis=0)
model.set_tensor(input_details[0]['index'], audio_input)
model.invoke()
output_data = model.get_tensor(output_details[0]['index'])
command_index = int(output_data.argmax())
commands = ["turn off", "turn on"]
if command_index < len(commands): return commands[command_index] else: return "unknown" while True: command = final_process_audio() print(f"Recognized command: {command}") if command == "turn on": led.on() print("LED successfully turned on.") elif command == "turn off": led.off() print("LED successfully turned off.") else: print("Unknown command received.") time.sleep(1) ```
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