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Verified signatureThis is the model used in the papers * N. Mousavi and F. Burkhardt: The Emotional Portrayal of an Ordinary Talk, Proc. ESSV 2026 * Mousavi, Burkhardt and Schuller: Modeling Emotion in German Ordinary Speech, to be published We used the embeddings of a transformer model that give emotional dimension values (trained on MSPPodcast: [audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim](https://huggingface.co/audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim)) to train a Multi Layer Perceptron with layers = [1024, 64] , default learning rate (.0001) and Adam optimizer, no dropout, patience set to 10. With the [nkululeko framework](https://github.com/felixbur/nkululeko) Training data was the test set of [Berlin Emodb](https://zenodo.org/records/17651657) and the whole of [Italian Emovo](https://aclanthology.org/L14-1478/) database, for classification from audio to ["happy", "angry", "sad", "scared", "neutral"]. Cross-domain evaluation with [Ravdess database](https://zenodo.org/record…e9010e3 -
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