Audio CAPTCHA Solver Using Machine Learning | Deep Learning Project | TensorFlow & Python
📞 For inquiries and collaboration opportunities, please contact us at +91 7676409450
🎯 Project Overview:
This video demonstrates a complete Audio CAPTCHA Prediction System built using Machine Learning and Deep Learning techniques. The project uses TensorFlow/Keras for neural network training, librosa for audio feature extraction (MFCC), and Streamlit for an interactive web interface.
🔬 Key Features:
✅ Real-time audio CAPTCHA digit prediction
✅ Support for both predefined samples and custom audio uploads
✅ MFCC (Mel-Frequency Cepstral Coefficients) feature extraction
✅ Deep learning model with confidence visualization
✅ Interactive Streamlit web application
✅ Professional UI with gradient backgrounds
🛠️ Technologies Used:
• Python 3.9
• TensorFlow & Keras (Deep Learning)
• librosa (Audio Processing)
• Streamlit (Web Interface)
• NumPy, SciPy (Data Processing)
• MFCC Feature Extraction
📚 What You'll Learn:
How to preprocess audio files for machine learning
Extracting MFCC features from audio signals
Building and training a neural network for audio classification
Creating an interactive web app with Streamlit
Real-time prediction with confidence scores
💻 Project Structure:
Audio preprocessing pipeline
Deep learning model architecture
Web interface development
Model deployment and inference
🎓 Perfect For:
Machine Learning enthusiasts
Deep Learning students
Python developers
Audio processing researchers
Computer Science students working on ML projects
📊 Use Cases:
CAPTCHA solving systems
Audio digit recognition
Speech recognition applications
Educational ML projects
Research in audio classification
🔗 Project Files:
Complete source code
Trained model (best_audio_model.keras)
Dataset for training
Requirements.txt with all dependencies
⚙️ Installation & Setup:
1. Install Python 3.9
2. Install dependencies from requirements.txt
3. Load the trained model
4. Run the Streamlit app
5. Upload or select audio samples for prediction
🎬 Video Chapters:
0:00 - Introduction
0:30 - Project Overview
1:15 - Technology Stack
2:00 - Audio Preprocessing
3:00 - Model Architecture
4:00 - Web Interface Demo
5:00 - Live Predictions
6:00 - Code Walkthrough
7:00 - Results & Analysis
💡 Don't forget to:
👍 Like this video if you found it helpful
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💬 Comment your questions below
📤 Share with fellow developers
#MachineLearning #DeepLearning #AudioProcessing #CAPTCHA #TensorFlow #Python #Streamlit #NeuralNetworks #AI #DataScience #PythonProjects #MLProjects #AudioClassification #MFCC #Librosa #Keras #ArtificialIntelligence
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📧 Contact: +91 7676409450
🔗 Connect for project collaboration and inquiries
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