Open-source voice model for deepfake audio detection - High-accuracy recognition of deepfake audio

Deepfake Audio Detection

Developed by motheecreator

A speech processing model further fine-tuned based on wav2vec2-base-finetuned, achieving 98.82% accuracy on the evaluation set

Speech Recognition

Transformers

Open Source License:Apache-2.0 #Speech Recognition #High Accuracy #Fine-tuning Optimization

Downloads 1,468

Release Time : 5/18/2024

Model Overview

This model is a speech processing model based on the wav2vec2 architecture, fine-tuned twice, suitable for tasks such as speech recognition

Model Features

High Accuracy

Achieves 98.82% accuracy on the evaluation set, demonstrating excellent performance

Double Fine-tuning

Secondary fine-tuning based on an already fine-tuned model, potentially offering better task adaptability

Optimized Training

Utilizes carefully designed training hyperparameters, including learning rate scheduling and gradient accumulation

Model Capabilities

Speech Recognition

Audio Feature Extraction

Use Cases

Speech Processing

Speech-to-Text

Convert speech content into text

Highly accurate conversion results

Voice Command Recognition

Recognize voice commands and execute corresponding actions

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.1448	1.0	1900	0.9601	0.1447
0.0673	2.0	3800	0.9824	0.0817
0.0178	3.0	5700	0.9796	0.1054
0.0002	4.0	7600	0.9824	0.1074
0.0108	5.0	9500	0.9882	0.0829

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Deepfake Audio Detection

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 wav2vec2-base-finetuned-finetuned

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

🔧 Technical Details

Training procedure

Training hyperparameters

Training results

Framework versions

Contributors

📄 License