Term Project for DSP Course, IIT KGP
This project develops a speaker identification system using frequency components of voice signals.
We use a k-nearest neighbour classifer for speaker classification. Two feature vector(FV) encodings are analysed for this purpose:
- Pass through custom uniform/non uniformly spaced filter banks, and use energies of outputs as FVs.
- Use MFCC coefficients and pitch as FVs
We use a CNN to detect if the correct numerical code has been spoken.
MFCC Coefficients are used as FVs for the CNN.
Please refer to the report for a detailed analysis and results.
Joint Contributors: Ayan Chakraborty, A Jaaneshwaran