- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
In: Lecture Notes in Computer Science, 5096, S. 244-253
- Classification
-
Informatik
- Event
-
Veröffentlichung
- (where)
-
Augsburg
- (who)
-
Universität Augsburg
- (when)
-
2008
- Event
-
Veröffentlichung
- (where)
-
Berlin
- (who)
-
Springer
- (when)
-
2008
- Creator
- DOI
-
10.1007/978-3-540-69321-5_25
- URN
-
urn:nbn:de:bvb:384-opus4-767098
- 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:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Schuller, Björn
- Wöllmer, Martin
- Moosmayr, Tobias
- Ruske, Günther
- Rigoll, Gerhard
- Universität Augsburg
- Springer
Time of origin
- 2008
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More than fifty years of speech and language processing - the rise of computational paralinguistics and ethical demands
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Spectral and cepstral audio noise reduction techniques in speech emotion recognition
Scaling speech enhancement in unseen environments with noise embeddings
Automatische Emotionserkennung aus sprachlicher und manueller Interaktion
Speech analysis in the big data era
Switching linear dynamic models for recognition of emotionally colored and noisy speech
Effects of in-car noise-conditions on the recognition of emotion within speech
Speech augmentation via speaker-specific noise in unseen environment
Speech emotion recognition: two decades in a nutshell, benchmarks, and ongoing trends
Speaker, noise, and acoustic space adaptation for emotion recognition in the automotive environment
More than fifty years of speech and language processing - the rise of computational paralinguistics and ethical demands
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Enhancing spontaneous speech recognition with BLSTM features
Spectral and cepstral audio noise reduction techniques in speech emotion recognition