The study of human affective behavior requires capturing emotion expressions in diverse, naturalistic environments (in the “wild”) from different modalities, such as video, audio and text. Currently, there is a number of commercial and open-source tools which analyze human emotion expressions in single modalities. However, none of these tools combine state-of-the-art, open-source, and free solutions into one single workflow. For this reason, we developed the Multimodal Emotion eXpression Capture Amsterdam (MEXCA) pipeline. The pipeline is available as a Python package (see the GitHub repository). Details about the software can be found in our preprint and in the documentation.
| Nr. | Citation |
| 1 | Malte Luken, Kody Moodley, Eva Viviani, Christian Pipal, Gijs Schumacher (2024). MEXCA – A Simple and Robust Pipeline for Capturing Emotion Expressions in Faces, Vocalization, and Speech. Preprint |
