Using statistical methods to determine speech femininity/masculinity based on phonetic features
Project description
SpeechGenderAnalysis
Setup
MacOS
1. Setup Python:
python3.8 -m venv venv8
source venv8/bin/activate
pip3 install -r requirements-mac.txt
2. Configure plaidml
to use GPU:
plaidml-setup
3. Configure environment variables in the run script:
export KERAS_BACKEND="plaidml.keras.backend"
export tg_token="Your telegram token here"
Windows (CUDA)
1. Setup Python
python3.9 -m venv venv
.\venv\Scripts\activate
pip install -r requirements-win-cuda.txt
2. Install CUDA
- Install NVIDIA Drivers: https://www.nvidia.com/drivers
- Install CUDA 11.2 (for TensorFlow 2.7.0): https://developer.nvidia.com/cuda-toolkit-archive
- Download cuDNN 8.1: https://developer.nvidia.com/rdp/cudnn-archive
- Copy folders in
cudnn-11.2-windows-x64-v8.1.1.33\cuda
toC:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2
- Copy folders in
- Restart IntelliJ IDEA
3. Check Device List
python -c "from tensorflow.python.client import device_lib; print(device_lib.list_local_devices())"
Arch Linux (CUDA)
Python (3.9.11)
python -m venv venv
source ./venv/bin/activate
pip install -r requirements-win-cuda.txt
sudo pacman -S tensorflow-cuda
python -c "from tensorflow.python.client import device_lib; print(device_lib.list_local_devices())"
Project details
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