How To Use

• Clone this repository

git clone https://github.com/schaffen2004/RAFM_SER.git
cd RAFM_SER

• Create a conda environment and install requirements

conda create -n RAFM_SER python=3.8 -y
conda activate RAFM_SER
conda install pytorch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 pytorch-cuda=11.8 -c pytorch -c nvidia
pip install -r requirements.txt

• Dataset used in this project is IEMOCAP and ESD.

cd scripts && python preprocess.py -ds IEMOCAP --data_root ./data/IEMOCAP_full_release

• Before starting training, you need to modify the config file in the config folder. You can refer to the config file in the config folder for more details.

cd scripts && python train.py -cfg ../src/configs/hubert_base.py

• You can also find our pre-trained models in the [release].