A Comparative Cross Language View On Acted Databases Portraying Basic Emotions Utilising Machine Learning

F Burkhardt, A Hacker, U Reichel, H Wierstorf, F Eyben, BW Schuller, "A Comparative Cross Language View On Acted Databases Portraying Basic Emotions Utilising Machine Learning," in Proceedings of the Thirteenth Language Resources and Evaluation Conference, (2022). [ paper ]

Bibtex

@inproceedings{Burkhardt2022a,
    title     = {A Comparative Cross Language View On Acted Databases
                 Portraying Basic Emotions Utilising Machine Learning},
    author    = {Burkhardt, Felix and Hacker, Anabell and Reichel, Uwe
                 and Wierstorf, Hagen and Eyben, Florian and Schuller, Bj\"{o}rn W.},
    booktitle = {Proceedings of the Thirteenth Language Resources
                 and Evaluation Conference},
    publisher = {European Language Resources Association},
    address   = {Marseille, France},
    month     = {June},
    pages     = {1917--1924},
    year      = {2022}
}

Abstract

Since several decades emotional databases have been recorded by various laboratories. Many of them contain acted portrays of Darwin’s famous “big four” basic emotions. In this paper, we investigate in how far a selection of them are comparable by two approaches: on the one hand modeling similarity as performance in cross database machine learning experiments and on the other by analyzing a manually picked set of four acoustic features that represent different phonetic areas. It is interesting to see in how far specific databases (we added a synthetic one) perform well as a training set for others while some do not. Generally speaking, we found indications for both similarity as well as specificiality across languages.