Voice-Vertification 😃

Introduction

Feature Extractor

STFT

Mel Spec

MFCC

GMM and GMM-UBM

JFA

I-vector

D-vector

X-vector

Wav2vec

Backend model

VggVox

Attention Backend

Loss Functions

Contrastive Loss

Triplet Loss

GE2E loss

Dataset

• Data can be found at link
• You should follow the data directory as in ./data

Usage

• You can follow colab files in /notebooks (not final yet LOL) for quick end2end implementation.

• If you wanna make it complicated, just look through the code in src and try step by step (make sure you're in the right folder before run commands):

  • Looking through the data python3 utils.py

  • For preparing dataset brefore training: python3 build_data.py --data_root --training_pairs --max_wav_len

  • For training python3 train.py --n_mfcc --sample_rate --batch_size 64 --epoch_n --lin_neurons

  • For testing: python3 predict.py --limit

References

• Lots of useful tutroials Youtube Channel
• Paper GMM pdf
• Paper Adaptive GMM pdf
• Paper JFA pdf
• Paper I vector pdf
• Paper D vector pdf
• Paper X vector pdf
• Paper attention backend with x vector pdf
• Wav2vec pdf
• Ge2e Loss Paper pdf
• Vggvox Paper pdf