Multimodal Emotion Detection System

An end-to-end multimodal system to an end-to-end system to support the creation, evaluation, and analysis of uni/multimodal ED models for children with autism pre-configured to use the CALMED dataset. It supports two different type of input modalities, i.e. video and audio.

This system has the following features:

• Highly customisable configuration;
• Automated setup for training and testing large numbers of models;
• Recording of results, saving of trained models to later re-use;
• Support for the creation of ensemble ED models;
• Support for grouping, analysing and visualising results by querying over the evaluation metrics;
• Pre-configured to use the CALMED dataset, allowing a quick and easy start.

The system supports any combination of features and inputs described in the CALMED dataset paper.

Pre-requisites

• Python 3.8
• Docker

Installation

Development

1. Prepare the virtual environment (Create and activate virtual environment with venv).

python -m venv ./venv

source ./venv/bin/activate

2. Run the script

python app.py

Deployment with Docker

1. Build the images

docker compose build

2. Start the services

docker compose up -d

User Manual

1. Use the system annotation_tool to create the labels.
2. Use the system features_extraction to preprocess the features extracted from tools, e.g., OpenFace and OpenSMILE into groups and into correct time window.
3. Use the system split_dataset to split features and labels dataset into train, dev and test sets. The output from there will serve as input to this system.
4. Put the features/labels PKL files into the folder /dataset/video or /dataset/audio depending on the modality you want to use.

Configuration for each experiment

• classifier_model: the classifier model for the whole multimodal ED system, usually used together with early fusion method, or in case of just one modality.
• model (within modality): the classifier model for the specific modality, usually used together with late fusion type.

Run data experiments script

Run the script from the main folder /emotion_detection_system

• If you select a modality, you need to select at least one features type.

Licence

This repository is released under dual-licencing:

For non-commercial use of the Software, it is released under the 3-Cause BSD Licence.

For commercial use of the Software, you are required to contact the University of Galway to arrange a commercial licence.

Please refer to LICENSE.md file for details on the licence.

Citation

If you use any of the resources provided on this repository in any of your publications we ask you to cite the following work:

Sousa, Annanda, et al. "Introducing CALMED: Multimodal Annotated Dataset for Emotion Detection in Children with Autism." International Conference on Human-Computer Interaction. Cham: Springer Nature Switzerland, 2023.

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Author: Annanda Sousa

Author's contact: annanda.sousa@gmail.com

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