Pattern Recognition Lab 1

# Pattern Recognition Lab - MFCC Feature Analysis | Python Implementation

📘 In this video, I explain a Python implementation for pattern recognition using MFCC (Mel-frequency cepstral coefficients) features.

### Key Points Covered:
- Implementation of Euclidean distance calculation
- MFCC file reading and organization
- Pattern recognition with feature vectors
- Intra-class distance calculation
- Output formatting and result analysis

### Code Components:
- 🔍 File organization and class separation
- 📊 Distance calculation between feature vectors
- 💻 Error calculation and averaging
- 📋 Tabular result presentation

### Technical Details:
- Language: Python
- Libraries: os, math
- Input: MFCC feature files (.mfc)
- Output: Class-wise pattern analysis

### Use Cases:
- Speech Recognition
- Pattern Classification
- Feature Analysis
- Acoustic Model Evaluation

### Time Stamps:
00:00 - Introduction
02:00 - Code Structure Explanation
05:00 - MFCC File Reading
08:00 - Distance Calculation
12:00 - Pattern Recognition Logic
15:00 - Result Analysis
18:00 - Conclusion

#PatternRecognition #Python #MFCC #MachineLearning #SpeechProcessing #Programming

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Видео Pattern Recognition Lab 1 канала Ahsan Ullah