Can deep generative audio be emotional? Towards an approach for personalised emotional audio generation
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
In: IEEE MMSP 2019 - 21st International Workshop on Multimedia Signal Processing, 27-29 September 2019, Kuala Lumpur, Malaysia, S. 1-5
- Klassifikation
-
Informatik
- Ereignis
-
Veröffentlichung
- (wo)
-
Augsburg
- (wer)
-
Universität Augsburg
- (wann)
-
2019
- Ereignis
-
Veröffentlichung
- (wo)
-
Piscataway, NJ
- (wer)
-
IEEE
- (wann)
-
2019
- Beteiligte Personen und Organisationen
-
Hwang, Jenq-Neng
Chan, Chee Seng
Cheng, Wen-Huang
Wong, Lai-Kuan
Ong, SimYing
- DOI
-
10.1109/MMSP.2019.8901785
- URN
-
urn:nbn:de:bvb:384-opus4-658748
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:32 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
- Baird, Alice
- Amiriparian, Shahin
- Schuller, Björn
- Hwang, Jenq-Neng
- Chan, Chee Seng
- Cheng, Wen-Huang
- Wong, Lai-Kuan
- Ong, SimYing
- Universität Augsburg
- IEEE
Entstanden
- 2019
Ähnliche Objekte (12)
New avenues in audio intelligence: towards holistic real-life audio understanding
Interaction with the soundscape: exploring emotional audio generation for improved individual wellbeing
Audio-based recognition of bipolar disorder utilising capsule networks
Computer audition for emotional wellbeing
Towards cross-modal pre-training and learning tempo-spatial characteristics for audio recognition with convolutional and recurrent neural networks
Face mask recognition from audio: the MASC database and an overview on the mask challenge
Correction to: The perception of emotional cues by children in artificial background noise
auDeep: Unsupervised Learning of Representations from Audio with Deep Recurrent Neural Networks
Emotion recognition in public speaking scenarios utilising an LSTM-RNN approach with attention
The perception of emotional cues by children in artificial background noise
Is deception emotional? An emotion-driven predictive approach
Bag-of-deep-features: noise-robust deep feature representations for audio analysis
New avenues in audio intelligence: towards holistic real-life audio understanding
Interaction with the soundscape: exploring emotional audio generation for improved individual wellbeing
Audio-based recognition of bipolar disorder utilising capsule networks
Computer audition for emotional wellbeing
Towards cross-modal pre-training and learning tempo-spatial characteristics for audio recognition with convolutional and recurrent neural networks
Face mask recognition from audio: the MASC database and an overview on the mask challenge
Correction to: The perception of emotional cues by children in artificial background noise
auDeep: Unsupervised Learning of Representations from Audio with Deep Recurrent Neural Networks
Emotion recognition in public speaking scenarios utilising an LSTM-RNN approach with attention
The perception of emotional cues by children in artificial background noise
Is deception emotional? An emotion-driven predictive approach
Bag-of-deep-features: noise-robust deep feature representations for audio analysis
New avenues in audio intelligence: towards holistic real-life audio understanding
Interaction with the soundscape: exploring emotional audio generation for improved individual wellbeing
Audio-based recognition of bipolar disorder utilising capsule networks
Computer audition for emotional wellbeing
Towards cross-modal pre-training and learning tempo-spatial characteristics for audio recognition with convolutional and recurrent neural networks
Face mask recognition from audio: the MASC database and an overview on the mask challenge
Correction to: The perception of emotional cues by children in artificial background noise
auDeep: Unsupervised Learning of Representations from Audio with Deep Recurrent Neural Networks
Emotion recognition in public speaking scenarios utilising an LSTM-RNN approach with attention
The perception of emotional cues by children in artificial background noise
Is deception emotional? An emotion-driven predictive approach