Synthetic Speech Classification: IEEE Signal Processing Cup 2022 challenge
Sound
2024-12-19 v1 Audio and Speech Processing
Abstract
The aim of this project is to implement and design arobust synthetic speech classifier for the IEEE Signal ProcessingCup 2022 challenge. Here, we learn a synthetic speech attributionmodel using the speech generated from various text-to-speech(TTS) algorithms as well as unknown TTS algorithms. Weexperiment with both the classical machine learning methodssuch as support vector machine, Gaussian mixture model, anddeep learning based methods such as ResNet, VGG16, and twoshallow end-to-end networks. We observe that deep learningbased methods with raw data demonstrate the best performance.
Cite
@article{arxiv.2412.13279,
title = {Synthetic Speech Classification: IEEE Signal Processing Cup 2022 challenge},
author = {Mahieyin Rahmun and Rafat Hasan Khan and Tanjim Taharat Aurpa and Sadia Khan and Zulker Nayeen Nahiyan and Mir Sayad Bin Almas and Rakibul Hasan Rajib and Syeda Sakira Hassan},
journal= {arXiv preprint arXiv:2412.13279},
year = {2024}
}