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Jabberjay

🦜 Synthetic Voice Detection

Models

Vision Transformer

Name Model Dataset Visualisation Model
MattyB95/VIT-ASVspoof2019-ConstantQ-Synthetic-Voice-Detection ViT ASVspoof2019 ConstantQ Hugging Face
MattyB95/VIT-ASVspoof2019-Mel_Spectrogram-Synthetic-Voice-Detection ViT ASVspoof2019 MelSpectrogram Hugging Face
MattyB95/VIT-ASVspoof2019-MFCC-Synthetic-Voice-Detection ViT ASVspoof2019 MFCC Hugging Face
MattyB95/VIT-ASVspoof5-ConstantQ-Synthetic-Voice-Detection ViT ASVspoof5 ConstantQ Hugging Face
MattyB95/VIT-ASVspoof5-Mel_Spectrogram-Synthetic-Voice-Detection ViT ASVspoof5 MelSpectrogram Hugging Face
MattyB95/VIT-ASVspoof5-MFCC-Synthetic-Voice-Detection ViT ASVspoof5 MFCC Hugging Face
MattyB95/VIT-VoxCelebSpoof-ConstantQ-Synthetic-Voice-Detection ViT VoxCelebSpoof ConstantQ Hugging Face
MattyB95/VIT-VoxCelebSpoof-Mel_Spectrogram-Synthetic-Voice-Detection ViT VoxCelebSpoof MelSpectrogram Hugging Face
MattyB95/VIT-VoxCelebSpoof-MFCC-Synthetic-Voice-Detection ViT VoxCelebSpoof MFCC Hugging Face

Audio Spectrogram Transformer

Name Model Dataset Model
MattyB95/AST-ASVspoof2019-Synthetic-Voice-Detection AST ASVspoof2019 Hugging Face
MattyB95/AST-ASVspoof5-Synthetic-Voice-Detection AST ASVspoof5 Hugging Face
MattyB95/AST-VoxCelebSpoof-Synthetic-Voice-Detection AST VoxCelebSpoof Hugging Face

Other

Name Paper Codebase Model
Classical Placeholder Placeholder Placeholder
RawNet2 End-to-End anti-spoofing with RawNet2 rawnet2-antispoofing pre_trained_DF_RawNet2.zip

Usage

Command Line Interface

usage: Jabberjay [-h] [-m {AST,Classical,RawNet2,VIT}]
                 [-d {ASVspoof2019,ASVspoof5,VoxCelebSpoof}]
                 [-vis {ConstantQ,MelSpectrogram,MFCC}] [-v]
                 audio

Python API

from Jabberjay.Utilities.enum_handler import Visualisation, Model, Dataset
from Jabberjay.jabberjay import Jabberjay

jabberjay = Jabberjay()

bonafide = jabberjay.load(filename="../res/bonafide/bonafide.flac")
spoof = jabberjay.load(filename="../res/spoof/spoof.flac")

jabberjay.detect(audio=bonafide, model=Model.VIT, visualisation=Visualisation.ConstantQ, dataset=Dataset.VoxCelebSpoof)
jabberjay.detect(audio=spoof, model=Model.VIT, visualisation=Visualisation.ConstantQ, dataset=Dataset.VoxCelebSpoof)

Contributing to Jabberjay

🌟 We value your contributions!

Whether you're fixing a bug, improving the documentation, or proposing a new feature, we're delighted to have you as part of the Jabberjay community. Your efforts help us make Synthetic Voice Detection even better for everyone.

We especially welcome and encourage additional models for speech deepfake (bonafide vs. spoof) detection, with the aim of making Jabberjay the one-stop shop for state-of-the-art models in the field.

We are truly grateful for your interest in improving Jabberjay. Your contributions, no matter how big or small, make our open-source community a vibrant place to learn, inspire, and create.

Let's make Jabberjay the best tool for Synthetic Voice Detection together! 🚀

Acknowledgement

This work was supported, in whole or in part, by the Bill & Melinda Gates Foundation [INV-001309].