TY - GEN
T1 - Spoken affect classification using neural networks
AU - Morrison, Donn
AU - Wang, Ruili
AU - De Silva, Liyanage C.
PY - 2005
Y1 - 2005
N2 - This paper aims to build an affect recognition system by analysing acoustic speech signals. A database of 391 authentic emotional utterances was collected from 11 speakers. Two emotions, angry and neutral, were considered. Features relating to pitch, energy and rhythm were extracted and used as feature vectors for a neural network. Forward selection was employed to prune redundant and harmful inputs. Initial results show a classification rate of 86.1%.
AB - This paper aims to build an affect recognition system by analysing acoustic speech signals. A database of 391 authentic emotional utterances was collected from 11 speakers. Two emotions, angry and neutral, were considered. Features relating to pitch, energy and rhythm were extracted and used as feature vectors for a neural network. Forward selection was employed to prune redundant and harmful inputs. Initial results show a classification rate of 86.1%.
UR - http://www.scopus.com/inward/record.url?scp=33845299830&partnerID=8YFLogxK
U2 - 10.1109/GRC.2005.1547359
DO - 10.1109/GRC.2005.1547359
M3 - Conference contribution
AN - SCOPUS:33845299830
SN - 0780390172
SN - 9780780390171
T3 - 2005 IEEE International Conference on Granular Computing
SP - 583
EP - 586
BT - 2005 IEEE International Conference on Granular Computing
T2 - 2005 IEEE International Conference on Granular Computing
Y2 - 25 July 2005 through 27 July 2005
ER -