/AudioDeepFakeDetection

Application that detects the authenticity of audio files developed using the Random Forest Model.

Primary LanguagePythonMIT LicenseMIT

AudioDeepFakeDetection

Application that detects the originality of audio files with artificial intelligence.

Setup Environment

# Make sure your PIP is up to date
pip install -U pip wheel setuptools

# Install required dependencies
pip install -r requirements.txt

Setup Datasets

You may download the datasets used in the project from the following URL:

https://drive.google.com/file/d/1O_PckJtEbQWlHEMSA5gDdxRooa1S1N2p/view

  • (Real) Human Voice Dataset:
    • This dataset consists of 10.000 short audio clips of a single speaker reading passages from 7 non-fiction books.
  • (Fake) Synthetic Voice Dataset:
    • The dataset consists of fake audio clips (16-bit PCM wav).

After downloading the datasets, you may extract them under data/real and data/fake respectively. In the end, the data directory should look like this:

data
├── real
    └── LJ001-0001
    └── LJ001-0002
    └── LJ001-0003
    └── LJ001-0004
    └── LJ001-0005
    └── LJ001-0006
    ...
└── fake
    └── LJ001-0001_gen
    └── LJ001-0002_gen
    └── LJ001-0003_gen
    └── LJ001-0004_gen
    └── LJ001-0005_gen
    └── LJ001-0006_gen
    ...

Application

You can run the file named main.py and load your audio file and test whether the file is real or not.

start

License

Our project is licensed under the MIT License.