1. Customer Satisfaction Based on Voice
Siyamamkela Bomela
Supervisor: Reg Dodds
Co-supervisor: Mehrdad Ghaziasgar

2. Overview Quick Recap Implementation Process
MFCC Feature Visual Representation
Training
Tools Used
References
Demo

3. Quick Recap

4. Implementation Read audio file MFCC Training Fast Fourier Transform
Mel Scale Filtering
Logarithm
Discrete Cosine Function
Training

5. MFCC Features Visual Representation

6. Training and Optimization
Support vector machine
Supervised training
Three classes
Feed data into SVM
Label data correctly
Cross validation
Uses radial basis function (RBF) kernel

7. Tools Used

8. Project Plan Term 1: Requirements Analysis Research on topic
Get dataset
Install Python
Understand Algorithms
Term 2: System Design
Develop a prototype
Term 3: Implementation
Finish coding the system
Term 4: Improving and Testing the system
Test the system for any errors and improve functionality of system where possible

9. References
[1] Wu, Z. and Cao, Z. (2005). Improved MFCC-based feature for robust speaker identification. Tsinghua Science and Technology, 10(2), pp
[2] Singh, S. and Rajan, E. (2011). MFCC VQ based Speaker Recognition and Its Accuracy Affecting Factors. International Journal of Computer Applications, 21(6), pp.1-6.

10. Demo