CCA based feature selection with application to continuous depression recognition from acoustic speech features
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
In: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 4-9 May 2014, Florence, Italy, S. 3729-3733
- Klassifikation
-
Informatik
- Ereignis
-
Veröffentlichung
- (wo)
-
Augsburg
- (wer)
-
Universität Augsburg
- (wann)
-
2014
- Ereignis
-
Veröffentlichung
- (wo)
-
Piscataway, NJ
- (wer)
-
IEEE
- (wann)
-
2014
- Urheber
- DOI
-
10.1109/icassp.2014.6854298
- URN
-
urn:nbn:de:bvb:384-opus4-725480
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 15.08.2025, 07:36 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Kaya, Heysem
- Eyben, Florian
- Salah, Albert Ali
- Schuller, Björn
- Universität Augsburg
- IEEE
Entstanden
- 2014
Ähnliche Objekte (12)
Likability of human voices: a feature analysis and a neural network regression approach to automatic likability estimation
On-line continuous-time music mood regression with deep recurrent neural networks
Single-channel speech separation with memory-enhanced recurrent neural networks
openSMILE:): the Munich open-source large-scale multimedia feature extractor
Robust feature extraction for automatic recognition of vibrato singing in recorded polyphonic music
Automatic multi-lingual arousal detection from voice applied to real product testing applications
Deep neural networks for anger detection from real life speech data
Combining long short-term memory and dynamic Bayesian networks for incremental emotion-sensitive artificial listening
iHEARu-PLAY: introducing a game for crowdsourced data collection for affective computing
Multi-resolution linear prediction based features for audio onset detection with bidirectional LSTM neural networks
Towards a standard set of acoustic features for the processing of emotion in speech
Convolutional RNN: an enhanced model for extracting features from sequential data
Likability of human voices: a feature analysis and a neural network regression approach to automatic likability estimation
On-line continuous-time music mood regression with deep recurrent neural networks
Single-channel speech separation with memory-enhanced recurrent neural networks
openSMILE:): the Munich open-source large-scale multimedia feature extractor
Robust feature extraction for automatic recognition of vibrato singing in recorded polyphonic music
Automatic multi-lingual arousal detection from voice applied to real product testing applications
Deep neural networks for anger detection from real life speech data
Combining long short-term memory and dynamic Bayesian networks for incremental emotion-sensitive artificial listening
iHEARu-PLAY: introducing a game for crowdsourced data collection for affective computing
Multi-resolution linear prediction based features for audio onset detection with bidirectional LSTM neural networks
Towards a standard set of acoustic features for the processing of emotion in speech
Convolutional RNN: an enhanced model for extracting features from sequential data
Likability of human voices: a feature analysis and a neural network regression approach to automatic likability estimation
On-line continuous-time music mood regression with deep recurrent neural networks
Single-channel speech separation with memory-enhanced recurrent neural networks
openSMILE:): the Munich open-source large-scale multimedia feature extractor
Robust feature extraction for automatic recognition of vibrato singing in recorded polyphonic music
Automatic multi-lingual arousal detection from voice applied to real product testing applications
Deep neural networks for anger detection from real life speech data
Combining long short-term memory and dynamic Bayesian networks for incremental emotion-sensitive artificial listening
iHEARu-PLAY: introducing a game for crowdsourced data collection for affective computing
Multi-resolution linear prediction based features for audio onset detection with bidirectional LSTM neural networks
Towards a standard set of acoustic features for the processing of emotion in speech