Making a Captcha Alternative for the Visually Impaired with Machine Learning

Visually impaired individuals face significant accessibility challenges when encountering visual-based CAPTCHAs, here machine learning can be ustilized to create a captcha alternative for visually impaireds.

This article explores an alternative solution for captcha that harness the power of machine learning. By making use of the machine leraning algorithms and adaptive technologies, we aim to bridge the gap, and ensuring equal access and user experience for the visually impaireds.


  • Python  Make sure that Python is installed on the system. The program is compatible with both Python 2 and Python 3.

  • Required Libraries  The program uses the following libraries, which need to be installed −

  • pyttsx3  It is used for text-to-speech conversion. We can install it using the command

pip install pyttsx3.
  • speech_recognition  It is used for speech recognition. Install it with

pip install SpeechRecognition
  • Microphone  The program requires a microphone to capture the user's speech input. Make sure the system has a functional microphone properly connected.

Making a Captcha Alternative for Visually Impaireds

We will be creating a model for a simple CAPTCHA (Completely Automated Public Turning test to tell Computers and Humans Apart) alternative using the text-to-speech functionalities and speech recognition. It allows us to generate a random string of characters and after that test their ability to recognize and enter those characters correctly.

Below are the steps that we will follow to create the model that will creaye a CAPTCHA alternative −

Step 1: Import the Required Libraries

We will be importing the following libraries −

  • random  This library is used to generate random numbers.

  • string  This library is used to work with strings.

  • pyttsx3  This library is used to convert text to speech.

  • speech_recognition  This library is used to recognize speech.

Step 2: Generate a Random String that contains Characters

Create and define a function called “generate_random_string” that takes a parameter called length. It uses the string and the random libraries to create a random sequence of alphanumeric characters of a specific length. This particular function is mainly responsible for generating the CAPTCHA alternative.

Step 3: Convert Text to Speech

Define a function with the function name “text_to_speech” that uses the pyttsx3 library to convert text into audible speech. It mainly initializes the text_to_speech engine, sets the rate of speech, and plays the specified text as audio.

Step 4: Perform the Speech Recognition

Define a function with the function name “recognize_speech” that utilizes the speech_recognition library to recognize speech input given by the user. It initializes a recognizer and a microphone source. The user is then prompted to speak the characters they hear, and the audio is recorded or captured using the microphone. The audio is then processed using Google Speech Recognition API to convert it into recognized text.

Step 5:Generate CAPTCHA Alternative and Validate

Define a function with the function name “generate_captcha_alternative” that combines the functions that were previously defined. It generates a random string using the “generate_random_string” function and displays it as the CAPTCHA alternative. The text is then converted into audio or speech using the function “text_to_speech” prompting the user to enter the characters they heard. The user’s speech is then recognized using the function “recognize_speech” function. If the text that is recognized matches the generated random string, a success message is spoken and displayed.

Step 6: Execute the Main Program

Last step is to check if the program is being run directly (as opposed to being imported as a module). If it is the main program, it calls the "generate_captcha_alternative" function to initiate the CAPTCHA alternative process.


import random
import string
import pyttsx3
import speech_recognition as sr

# Generate a random string of characters
def generate_random_string(length):
   letters = string.ascii_letters + string.digits
   return ''.join(random.choice(letters) for _ in range(length))

# Convert text to speech
def text_to_speech(text):
   engine = pyttsx3.init()
   engine.setProperty('rate', 150)

# Speech recognition
def recognize_speech():
   r = sr.Recognizer()
   with sr.Microphone() as source:
      print("Please say the characters you hear...")
         audio = r.listen(source)
         recognized_text = r.recognize_google(audio)
         return recognized_text.lower()
      except sr.UnknownValueError:
         print("Sorry, I could not understand your speech.")
         return ""
      except sr.RequestError:
         print("Sorry, speech recognition service is currently unavailable.")
         return ""

# Generate CAPTCHA alternative
def generate_captcha_alternative():
   random_string = generate_random_string(6)
   print("Generated CAPTCHA alternative:", random_string)
   text_to_speech("Please enter the characters you hear")
   recognized_text = recognize_speech()
   if recognized_text == random_string.lower():
      print("Success! You have entered the correct characters.")
      text_to_speech("Success! You have entered the correct characters.")
      print("Incorrect characters entered.")
      text_to_speech("Incorrect characters entered.")

# Main program
if __name__ == "__main__":
Write prerequisites for the above program




In conclusion, by making use of machine learning algorithms and techniques, we can create an alternative to CAPTCHA for the visually impaired. This alternative method uses text-to-speech conversion and speech recognition to provide an inclusive and accessible verification process. Such innovations empower visually impaired individuals to overcome the challenges posed by traditional visual CAPTCHAs, ensuring equal access to online services and platforms.

Updated on: 11-Jul-2023


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