Data

Tools

Indexes

Applications

Experiments

Open Source Science

088-temporal-channel-modeling-in-multi-head-self-attention-for-synthetic-speech-detection

https://github.com/szu-advtech-2024/088-temporal-channel-modeling-in-multi-head-self-attention-for-synthetic-speech-detection

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (4.6%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: SZU-AdvTech-2024
  • Default Branch: main
  • Size: 0 Bytes
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Citation

https://github.com/SZU-AdvTech-2024/088-Temporal-Channel-Modeling-in-Multi-head-Self-Attention-for-Synthetic-Speech-Detection/blob/main/ 

# Temporal-Channel Modeling in Multi-head Self-Attention for Synthetic Speech Detection

## Pretrained Model
The pretrained model XLSR can be found at [link](https://dl.fbaipublicfiles.com/fairseq/wav2vec/xlsr2_300m.pt).

## Setting up environment
Python version: 3.7.16

Install PyTorch
```bash
pip install torch==1.8.1+cu111 torchvision==0.9.1+cu111 torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html
```
Install other libraries:
```bash
pip install -r requirements.txt
```

## Training & Evaling
To train and produce the score, run:
```bash
python main.py --algo 5 --device your_device # For LA track evaluation
python main.py --algo 3 --device your_device # For DF track evaluation
```

## Evaling with a pretrained model
To eval a pretrained model, run:
```bash
python main.py --algo 3 --device your_device --ckpt_path your_model_path.pth
```

## Scoring
To get evaluation results of minimum t-DCF and EER (Equal Error Rate), follow these steps:
```bash
cd 2021/eval-package
python main.py --cm-score-file your_LA_score.txt --track LA --subset eval # For LA track evaluation
python main.py --cm-score-file your_DF_score.txt --track DF --subset eval # For DF track evaluation
```

Owner

  • Name: SZU-AdvTech-2024
  • Login: SZU-AdvTech-2024
  • Kind: organization

GitHub Events

Total
  • Push event: 2
  • Create event: 3
Last Year
  • Push event: 2
  • Create event: 3