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Hubert Base 960h Asv19 Deepfake
An audio classification model based on the HuBERT architecture, specifically designed for detecting deepfake audio and audio spoofing
Downloads 15
Release Time : 3/13/2024
Model Overview
This model is a fine-tuned version of facebook/hubert-base-ls960, focusing on audio classification tasks, particularly the detection of deepfake audio.
Model Features
High Accuracy
Achieves 99.18% accuracy on the evaluation set
Low Error Rate
Equal Error Rate (EER) is only 0.56%
Based on HuBERT Architecture
Utilizes the powerful speech representation learning capability of HuBERT
Model Capabilities
Audio Classification
Deepfake Detection
Audio Spoofing Recognition
Use Cases
Security Detection
Voice Authentication System
Detect forged audio in voice authentication systems
Can effectively identify over 99% of forged audio
Content Moderation
Identify forged audio content on social media
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