We present an approach for the prediction of valence, arousal, and dominance of people communicating via text/audio/video streams for a translation from and to sign languages. 

The approach consists of the fusion of the output of three CNN-based models dedicated to the analysis of text, audio, and facial expressions. Our experiments show that any combination of two or three modalities increases prediction performance for valence and arousal 

Doi 10.14428/esann/2023.ES2023-128