Fake-Voice-Detection

Author: Jingqiu Ding, Kei Ishikawa, Xiaoran Chen. The original code for Cyclic GAN is by Lei Mao.

Environment: ubuntu 18.04, Python 3.6

Converted Voice Sample

id	real	fake
200001	link: ./converted_samples/200001_real.wav	link: ./converted_samples/200001_fake.wav
200002	link: ./converted_samples/200002_real.wav	link: ./converted_samples/200002_fake.wav
200003	link: ./converted_samples/200003_real.wav	link: ./converted_samples/200003_fake.wav
200004	link: ./converted_samples/200004_real.wav	link: ./converted_samples/200004_fake.wav
200005	link: ./converted_samples/200005_real.wav	link: ./converted_samples/200005_fake.wav

* depending on the browser, you cannot play the wav files on the browser.

plot of Score* for GMM-based verification system

* "score" is the log likelihood ratio of the GMM-Speakermodel and the GMM-UBG model.

• test ... Obama's voice which is not used for training neither conversion system or verificationsystem
• fake ... fake voice of Obama generated by voice conversion system (cycle GAN)
• universal background ... voice from a lot of people

(FOR LEONHARD CLUSTER)

run the following at .../Fake-Voice-Detection/

source ./set_env_leonhard.sh
bsub -W 4:00 -R "rusage[ngpus_excl_p=1,mem=16000]" source ./run_all_leonhard.sh

Introduction

Files

.
├──src
│   ├──conversion
│   │   ├─ model.py
│   │   ├─ module.py
│   │   ├─ preprocess.py
│   │   ├─ train.py
│   │   └─ utils.py
│   ├──verification_gmm
│   │   ├─ compute_auc.py
│   │   └─ train_and_plot.py
│   ├── verification_vae
│   │   ├─ cvae_verification.py
│   │   └─ cvae_keras.py
│   ├── download.py
│   └── split_normalize_raw_speech.py.py
│
├──data
│   ├──target_raw (Obama)
│   ├──target (Obama)
│   │   ├─ train_conversion
│   │   ├─ train_verification
│   │   └─ test
│   ├──source
│   │   └─ train_conversion
│   └──ubg
│       ├─ train_verification
│       └─ test
├──out
│   ├──plot
│   └──scores
├── set_env_leonhard.sh
├── run_all_leonhard.sh
├── README.md

Requirments

Install all the requirements (except numpy, matplotlib, scikitlearn, tensorflow).

pip install --user -r requirements.txt

If librosa gives backend error, run following. (This is module load ffmpeg in HPC cluster in ETH.)

apt-get install ffmpeg

Usage

run the following at .../Fake-Voice-Detection/

Download Dataset and preprocess

Download and unzip datasets and pretrained models.

$ python ./src/download.py

Split the raw speech

$ python ./src/split_normalize_raw_speech.py

CycleGAN Voice Conversion

Train the Voice Conversion Model

$ python ./src/conversion/train.py --model_dir='./model/conversion/pretrained'

Convert the source speaker's voice

$ python ./src/conversion/convert.py --model_dir='./model/conversion/pretrained'

GMM-UBG verification

Train the GMM based verification system and Plot the scores

$ python ./src/verification_gmm/train_and_plot.py

compute AUC converted samples of every 50 epoch

$ python ./src/verification_gmm/compute_auc.py

Convolutional VAE

Train the CVAE based verification system and Plot the scores

$ python ./src/verification_cvae/cvae_verification.py