TY - GEN
T1 - Towards more reality in the recognition of emotional speech
AU - Schuller, Björn
AU - Seppi, Dino
AU - Batliner, Anton
AU - Maier, Andreas
AU - Steidl, Stefan
PY - 2007
Y1 - 2007
N2 - As automatic emotion recognition based on speech matures, new challenges can be faced. We therefore address the major aspects in view of potential applications in the field, to benchmark today's emotion recognition systems and bridge the gap between commercial interest and current performances: acted vs. spontaneous speech, realistic emotions, noise and microphone conditions, and speaker independence. Three different data-sets are used: the Berlin Emotional Speech Database, the Danish Emotional Speech Database, and the spontaneous AIBO Emotion Corpus. By using different feature types such as word- or turn-based statistics, manual versus forced alignment, and optimization techniques we show how to best cope with this demanding task and how noise addition or different microphone positions affect emotion recognition.
AB - As automatic emotion recognition based on speech matures, new challenges can be faced. We therefore address the major aspects in view of potential applications in the field, to benchmark today's emotion recognition systems and bridge the gap between commercial interest and current performances: acted vs. spontaneous speech, realistic emotions, noise and microphone conditions, and speaker independence. Three different data-sets are used: the Berlin Emotional Speech Database, the Danish Emotional Speech Database, and the spontaneous AIBO Emotion Corpus. By using different feature types such as word- or turn-based statistics, manual versus forced alignment, and optimization techniques we show how to best cope with this demanding task and how noise addition or different microphone positions affect emotion recognition.
KW - Affective computing
KW - Emotion recognition
KW - Noise robustness
KW - Spontaneous emotions
UR - https://www.scopus.com/pages/publications/34547549142
U2 - 10.1109/ICASSP.2007.367226
DO - 10.1109/ICASSP.2007.367226
M3 - Conference contribution
AN - SCOPUS:34547549142
SN - 1424407281
SN - 9781424407286
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - IV941-IV944
BT - 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
T2 - 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Y2 - 15 April 2007 through 20 April 2007
ER -