Multiscale kernel locally penalised discriminant analysis exemplified by emotion recognition in speech
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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In: Proceedings of the 18th ACM International Conference on Multimodal Interaction, Tokyo, Japan, November 12 - 16, 2016, S. 233-237
- Event
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Veröffentlichung
- (where)
-
Augsburg
- (who)
-
Universität Augsburg
- (when)
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2016
- Event
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Veröffentlichung
- (where)
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New York, NY
- (who)
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ACM
- (when)
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2016
- Creator
- Contributor
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Nakano, Yukiko
- DOI
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10.1145/2993148.2993184
- URN
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urn:nbn:de:bvb:384-opus4-721583
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:20 AM CEST
Data provider
This object is provided by:
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Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Xu, Xinzhou
- Deng, Jun
- Gavryukova, Maryna
- Zhang, Zixing
- Zhao, Li
- Schuller, Björn
- Nakano, Yukiko
- Universität Augsburg
- ACM
Time of origin
- 2016
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Distributing recognition in computational paralinguistics
Identifying surgical-mask speech using deep neural networks on low-level aggregation
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Semisupervised autoencoders for speech emotion recognition
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Introducing shared-hidden-layer autoencoders for transfer learning and their application in acoustic emotion recognition
ACM guide to computing literature, 1983
ACM guide to computing literature, 1985
Autoencoder-based unsupervised domain adaptation for speech emotion recognition
Cooperative learning and its application to emotion recognition from speech
Recognizing emotions from whispered speech based on acoustic feature transfer learning
Distributing recognition in computational paralinguistics
Identifying surgical-mask speech using deep neural networks on low-level aggregation
Linked source and target domain subspace feature transfer learning - exemplified by speech emotion recognition
Exploitation of phase-based features for whispered speech emotion recognition
Semisupervised autoencoders for speech emotion recognition
Universum autoencoder-based domain adaptation for speech emotion recognition