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Emotional space improves emotion recognition
Abstract
A number of recent studies have focused on the conceptualized expression of emotions as a three-dimensional space. This paper proposes a new approach to emotion recognition, making use of two of the emotional dimensions and their relationship with different kinds of features. The main idea consists in associating prosodic features, derived from pitch, loudness, and duration, with the activation or arousal dimension, and quality features, i.e. phonation type, articulation manner, voice timbre, with the evaluation and pleasure dimension, in a way that different classification methods can be applied for each specific case. Most important results are achieved for the speaker-independent case and three classes, with a recognition rate close to 80%. 1.
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Cited by
Emotion Recognition Using Bio-sensors: First Steps towards an Automatic System
Haag, A., Goronzy, S., Schaich, P., & Williams, J. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24842-2_4 · Cited by 451
Zhang, S., Zhang, S., Huang, T., & Gao, W. (2018) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2017.2766843 · Cited by 441
(2013) · Cited by 236
A machine learning model for emotion recognition from physiological signals
Domínguez-Jiménez, J. A., Campo-Landines, K. C., Martínez-Santos, J. C., Delahoz, E. J., & Contreras-Ortiz, S. H. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2019.101646 · Cited by 232
Emotion Recognition based on Phoneme Classes
Lee, C. M., Yildirim, S., Bulut, M., Kazemzadeh, A., Busso, C., Deng, Z., Lee, S., & Narayanan, S. (2004) · Interspeech 2004 · doi:10.21437/interspeech.2004-322 · Cited by 228
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- Tato, R., Santos, R., Kompe, R., & Pardo, J. M. (2002). Emotional space improves emotion recognition. 7th International Conference on Spoken Language Processing (ICSLP 2002). https://doi.org/10.21437/icslp.2002-557
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