no code implementations • 4 Mar 2024 • Lucía Gómez-Zaragozá, Óscar Valls, Rocío del Amor, María José Castro-Bleda, Valery Naranjo, Mariano Alcañiz Raya, Javier Marín-Morales
The pre-trained Unispeech-L model and its combination with eGeMAPS achieved the highest results, with 61. 64% and 55. 57% Unweighted Accuracy (UA) for 3-class valence and arousal prediction respectively, a 10% improvement over baseline models.
no code implementations • 27 Feb 2024 • Lucía Gómez Zaragozá, Rocío del Amor, Elena Parra Vargas, Valery Naranjo, Mariano Alcañiz Raya, Javier Marín-Morales
For speech, we used the standard eGeMAPS feature set and support vector machines, obtaining 49. 27% and 44. 71% unweighted accuracy for valence and arousal respectively.