Emotion in the singing voice: a deeper look at acoustic features in the light of automatic classification
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
In: EURASIP Journal on Audio, Speech, and Music Processing, 2015, 1, S. 19-
- Ereignis
-
Veröffentlichung
- (wo)
-
Augsburg
- (wer)
-
Universität Augsburg
- (wann)
-
2015
- Ereignis
-
Veröffentlichung
- (wer)
-
Springer Science and Business Media LLC
- (wann)
-
2015
- Urheber
- DOI
-
10.1186/s13636-015-0057-6
- URN
-
urn:nbn:de:bvb:384-opus4-725112
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:50 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
- Eyben, Florian
- Salomão, Gláucia L.
- Sundberg, Johan
- Scherer, Klaus R.
- Schuller, Björn
- Universität Augsburg
- Springer Science and Business Media LLC
Entstanden
- 2015
Ähnliche Objekte (12)
The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing
Seeking the SuperStar: automatic assessment of perceived singing quality
Automatic multi-lingual arousal detection from voice applied to real product testing applications
Robust feature extraction for automatic recognition of vibrato singing in recorded polyphonic music
openSMILE:): the Munich open-source large-scale multimedia feature extractor
Prosodic, spectral or voice quality? Feature type relevance for the discrimination of emotion pairs
Voice analysis for neurological disorder recognition – a systematic review and perspective on emerging trends
VoicePlay: an affective sports game operated by speech emotion recognition based on the component process model
Tempo estimation and beat tracking with long short-term memory neural networks and comb-filters
Towards a standard set of acoustic features for the processing of emotion in speech
Specification of suitable parameters for emotion perception and definition of API for later integration
On-line continuous-time music mood regression with deep recurrent neural networks
The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing
Seeking the SuperStar: automatic assessment of perceived singing quality
Automatic multi-lingual arousal detection from voice applied to real product testing applications
Robust feature extraction for automatic recognition of vibrato singing in recorded polyphonic music
openSMILE:): the Munich open-source large-scale multimedia feature extractor
Prosodic, spectral or voice quality? Feature type relevance for the discrimination of emotion pairs
Voice analysis for neurological disorder recognition – a systematic review and perspective on emerging trends
VoicePlay: an affective sports game operated by speech emotion recognition based on the component process model
Tempo estimation and beat tracking with long short-term memory neural networks and comb-filters
Towards a standard set of acoustic features for the processing of emotion in speech
Specification of suitable parameters for emotion perception and definition of API for later integration
On-line continuous-time music mood regression with deep recurrent neural networks
The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing
Seeking the SuperStar: automatic assessment of perceived singing quality
Automatic multi-lingual arousal detection from voice applied to real product testing applications
Robust feature extraction for automatic recognition of vibrato singing in recorded polyphonic music
openSMILE:): the Munich open-source large-scale multimedia feature extractor
Prosodic, spectral or voice quality? Feature type relevance for the discrimination of emotion pairs
Voice analysis for neurological disorder recognition – a systematic review and perspective on emerging trends
VoicePlay: an affective sports game operated by speech emotion recognition based on the component process model
Tempo estimation and beat tracking with long short-term memory neural networks and comb-filters
Towards a standard set of acoustic features for the processing of emotion in speech
Specification of suitable parameters for emotion perception and definition of API for later integration