Synthetic Speech Detection
8 papers with code • 0 benchmarks • 2 datasets
Detect fake synthetic speech generated using machine learning
Benchmarks
These leaderboards are used to track progress in Synthetic Speech Detection
DEEP-VOICE: DeepFake Voice Recognition
Synthetic Speech Attribution
Most implemented papers
Replay and Synthetic Speech Detection with Res2net Architecture
lixucuhk/ASV-anti-spoofing-with-Res2Net
•
•
This multiple scaling mechanism significantly improves the countermeasure's generalizability to unseen spoofing attacks.
UR Channel-Robust Synthetic Speech Detection System for ASVspoof 2021
yzyouzhang/asvspoof2021_air
•
•
Different from previous ASVspoof challenges, the LA task this year presents codec and transmission channel variability, while the new task DF presents general audio compression.
ConvNeXt Based Neural Network for Audio Anti-Spoofing
With the rapid development of speech conversion and speech synthesis algorithms, automatic speaker verification (ASV) systems are vulnerable to spoofing attacks.
Towards End-to-End Synthetic Speech Detection
ghuawhu/end-to-end-synthetic-speech-detection
•
•
The constant Q transform (CQT) has been shown to be one of the most effective speech signal pre-transforms to facilitate synthetic speech detection, followed by either hand-crafted (subband) constant Q cepstral coefficient (CQCC) feature extraction and a back-end binary classifier, or a deep neural network (DNN) directly for further feature extraction and classification.
FMFCC-A: A Challenging Mandarin Dataset for Synthetic Speech Detection
As increasing development of text-to-speech (TTS) and voice conversion (VC) technologies, the detection of synthetic speech has been suffered dramatically.
Multi-task learning improves synthetic speech detection
mo666666/Multi-Task-Learning-Improves-Synthetic-Speech-Detection
•
•
2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2022) 2022
In this paper, by observing that deepening the network impairs the performance of the network in detecting unknown attacks, we propose that the synthetic speech detection problem is an out-of-distribution (OOD) generalization problem and we enhance the robustness of networks by using multi-task learning.
The Sound of Silence: Efficiency of First Digit Features in Synthetic Audio Detection
dan8991/the-sound-of-silence
•
•
The recent integration of generative neural strategies and audio processing techniques have fostered the widespread of synthetic speech synthesis or transformation algorithms.
SingFake: Singing Voice Deepfake Detection
These unique properties make singing voice deepfake detection a relevant but significantly different problem from synthetic speech detection.
