TY - GEN
T1 - Boǧaziçi üniversitesi türkçe duygulu konuşma veritabani üzerinde deneyler için protokol ve taban çizgis
AU - Kaya, Heysem
AU - Salali, Albert Ali
AU - Gurgen, Sadik Fikret
AU - Ekenel, Hazim
PY - 2014
Y1 - 2014
N2 - This study aims at presenting an emotional corpus collected at Boǧaziçi University / Electrical and Electronics Department, on which no previous signal processing and machine learning study was done for classification purposes. It also aims at providing the protocol for further experiments on this corpus. The emotional corpus consists of 484 speech utterances from 11 amateur actors acting 11 emotionally undefined sentences with 4 emotions using Stanislavsky effect. In-line with the state-of-the-art method in the field, functionals were passed over the Low Level Descriptors of the signal to obtain fixed length feature vectors. For this purpose, the openSMILE feature extractor was used with the baseline feature set from the INTERSPEECH 2013 Computational Paralinguistics Challenge. The training, validation and testing partitions are defined on the corpus. The baseline results obtained using Support Vector Machines and Random Forests are presented.
AB - This study aims at presenting an emotional corpus collected at Boǧaziçi University / Electrical and Electronics Department, on which no previous signal processing and machine learning study was done for classification purposes. It also aims at providing the protocol for further experiments on this corpus. The emotional corpus consists of 484 speech utterances from 11 amateur actors acting 11 emotionally undefined sentences with 4 emotions using Stanislavsky effect. In-line with the state-of-the-art method in the field, functionals were passed over the Low Level Descriptors of the signal to obtain fixed length feature vectors. For this purpose, the openSMILE feature extractor was used with the baseline feature set from the INTERSPEECH 2013 Computational Paralinguistics Challenge. The training, validation and testing partitions are defined on the corpus. The baseline results obtained using Support Vector Machines and Random Forests are presented.
KW - Computational Paralinguistics
KW - Emotional Speech Corpus
KW - Human-Computer Interaction
KW - Speech Emotion Recognition
UR - http://www.scopus.com/inward/record.url?scp=84903795060&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84903795060&partnerID=8YFLogxK
U2 - 10.1109/SIU.2014.6830575
DO - 10.1109/SIU.2014.6830575
M3 - Conference contribution
AN - SCOPUS:84903795060
SN - 9781479948741
T3 - 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings
SP - 1698
EP - 1701
BT - 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings
PB - IEEE Computer Society
T2 - 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014
Y2 - 23 April 2014 through 25 April 2014
ER -