Affective Naturalistic Database Consortium
Please make sure the following dependencies are installed before using this repository:
- openSMILE: https://www.audeering.com/research/opensmile/
- Montreal Forced Aligner: https://montreal-forced-aligner.readthedocs.io/en/latest/installation.html
- Whisper: https://github.com/openai/whisper
- Conda: https://docs.conda.io/en/latest/
Once all dependencies are installed, you can setup the different conda environments to be used by going to /ANDC/env_setup and running
bash create_conda_envs.sh
Additionally, you can download the models by running:
bash download_models.sh
Additionally we use "aligner" for the MFA environment as defined in MFA installer
- Create a directory and place all collected audio/video clips inside (i.e., /ANDC_batches/2023_7_29/audios)
- Run the script providing the batch directory
bash run.sh -r /ANDC_batches/2023_7_29
- All files will be saved inside the provided directory. Mainly Short_files.json will be created which aggregates all the information (segmentation, gender, music, SNR, emotions, etc). Furthermore, a directory will be created named Outputs which will contains the short and long audio clips as well as extracted features such as ASR.
- [:heavy_check_mark:] Add multiple emotional models to pipeline
- Add README file to each model used
- Improve code clarity
- Add details for the json files
- Add details on the file structure used in Outputs
- Remove extracted features once all inference has been complete
- Add GPU support
We highly encourage contribution to this repository. Feel free to fork it and add your own models and play with the code. We provide a template in /Template that can be used as the starting point. Once you develope your code, you can add the the run command and your own environment to the run.sh file. Finally, create a pull request if you want to contribute and share your models!
This project is licensed under the MIT License - see the LICENSE.md file for details