yasinfakhar / x-vector-anonymization-using-autoencoder-and-adversial-training-for-preserving-speech-privacy

this repository contains pytorch implementation of article "X-vector anonymization using autoencoders and adversarial training for preserving speech privacy"

x-vector-anonymization-using-autoencoder-and-adversial-training-for-preserving-speech-privacy

this repository contains pytorch implementation of article "X-vector anonymization using autoencoders and adversarial training for preserving speech privacy"

jornal = Computer Speech & Language (CSL)

year = 2022

authors = Juan M. Perero-Codosero, Fernando M. Espinoza-Cuadros, Luis A. Hernández-Gómez b

link to original paper

Notes :

• The authors of this article used x-vector but I used d-vector. They are all the same and are used for speaker embedding.
• I just implement the vector anonymization part
• I train on a much smaller dataset from Kaggle instead of VoxCeleb which is a huge dataset
• You only need an Kaggle.com account and request for an API key for downloading the dataset

Language and framework used :

• Python
• Pytorch