Abstract
The acquisition of naturalistic speech data and the richness of its annotation are very important to face the challenges of automatic emotion recognition from speech. This paper describes the creation of a database of emotional speech in the Spanish spoken in Mexico. It was recorded from children between 7 and 13 years old while playing a sorting card game with an adult examiner. The game is based on a neuropsychological test, modified to encourage dialogue and induce emotions in the player. The audio was segmented at speaker turn level and annotated with six emotional categories and three continuous emotion primitives by 11 human evaluators. Inter-evaluator agreement is presented for categorical and continuous annotation. Initial classification and regression experiments were performed using a set of 6,552 acoustic features.
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Pérez-Espinosa, H., Reyes-García, C.A., Villaseñor-Pineda, L. (2011). EmoWisconsin: An Emotional Children Speech Database in Mexican Spanish. In: D’Mello, S., Graesser, A., Schuller, B., Martin, JC. (eds) Affective Computing and Intelligent Interaction. ACII 2011. Lecture Notes in Computer Science, vol 6975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24571-8_7
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DOI: https://doi.org/10.1007/978-3-642-24571-8_7
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