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https://doi.org/10.21256/zhaw-1458
Publikationstyp: | Konferenz: Paper |
Art der Begutachtung: | Peer review (Publikation) |
Titel: | Emotion recognition from speech using representation learning in extreme learning machines |
Autor/-in: | Glüge, Stefan Böck, Ronald Ott, Thomas |
DOI: | 10.5220/0006485401790185 10.21256/zhaw-1458 |
Tagungsband: | Proceedings of the 9th International Joint Conference on Computational Intelligence |
Herausgeber/-in des übergeordneten Werkes: | Sabourin, Christophe Julian Merelo, Juan O'Reilly, Una-May Madani, Kurosh Warwick, Kevin |
Seite(n): | 179 |
Seiten bis: | 185 |
Angaben zur Konferenz: | 9th International Joint Conference on Computational Intelligence, Funchal, Portugal, 1-3 November 2017 |
Erscheinungsdatum: | 2017 |
Verlag / Hrsg. Institution: | SciTePress |
ISBN: | 978-989-758-274-5 |
Sprache: | Englisch |
Schlagwörter: | Emotion recognition from speech; Representation learning; Extreme learning machine |
Fachgebiet (DDC): | 006: Spezielle Computerverfahren |
Zusammenfassung: | We propose the use of an Extreme Learning Machine initialised as auto-encoder for emotion recognition from speech. This method is evaluated on three different speech corpora, namely EMO-DB, eNTERFACE and SmartKom. We compare our approach against state-of-the-art recognition rates achieved by Support Vector Machines (SVMs) and a deep learning approach based on Generalised Discriminant Analysis (GerDA). We could improve the recognition rate compared to SVMs by 3%-14% on all three corpora and those compared to GerDA by 8%-13% on two of the three corpora. |
URI: | https://digitalcollection.zhaw.ch/handle/11475/1519 |
Volltext Version: | Publizierte Version |
Lizenz (gemäss Verlagsvertrag): | CC BY-NC-ND 4.0: Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International |
Departement: | Life Sciences und Facility Management |
Organisationseinheit: | Institut für Computational Life Sciences (ICLS) |
Enthalten in den Sammlungen: | Publikationen Life Sciences und Facility Management |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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IJCCI_2017_3.pdf | 190.19 kB | Adobe PDF | Öffnen/Anzeigen |
Zur Langanzeige
Glüge, S., Böck, R., & Ott, T. (2017). Emotion recognition from speech using representation learning in extreme learning machines [Conference paper]. In C. Sabourin, J. Julian Merelo, U.-M. O’Reilly, K. Madani, & K. Warwick (Eds.), Proceedings of the 9th International Joint Conference on Computational Intelligence (pp. 179–185). SciTePress. https://doi.org/10.5220/0006485401790185
Glüge, S., Böck, R. and Ott, T. (2017) ‘Emotion recognition from speech using representation learning in extreme learning machines’, in C. Sabourin et al. (eds) Proceedings of the 9th International Joint Conference on Computational Intelligence. SciTePress, pp. 179–185. Available at: https://doi.org/10.5220/0006485401790185.
S. Glüge, R. Böck, and T. Ott, “Emotion recognition from speech using representation learning in extreme learning machines,” in Proceedings of the 9th International Joint Conference on Computational Intelligence, 2017, pp. 179–185. doi: 10.5220/0006485401790185.
GLÜGE, Stefan, Ronald BÖCK und Thomas OTT, 2017. Emotion recognition from speech using representation learning in extreme learning machines. In: Christophe SABOURIN, Juan JULIAN MERELO, Una-May O’REILLY, Kurosh MADANI und Kevin WARWICK (Hrsg.), Proceedings of the 9th International Joint Conference on Computational Intelligence. Conference paper. SciTePress. 2017. S. 179–185. ISBN 978-989-758-274-5
Glüge, Stefan, Ronald Böck, and Thomas Ott. 2017. “Emotion Recognition from Speech Using Representation Learning in Extreme Learning Machines.” Conference paper. In Proceedings of the 9th International Joint Conference on Computational Intelligence, edited by Christophe Sabourin, Juan Julian Merelo, Una-May O’Reilly, Kurosh Madani, and Kevin Warwick, 179–85. SciTePress. https://doi.org/10.5220/0006485401790185.
Glüge, Stefan, et al. “Emotion Recognition from Speech Using Representation Learning in Extreme Learning Machines.” Proceedings of the 9th International Joint Conference on Computational Intelligence, edited by Christophe Sabourin et al., SciTePress, 2017, pp. 179–85, https://doi.org/10.5220/0006485401790185.
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