Mоlimо vаs kоristitе оvај idеntifikаtоr zа citirаnjе ili оvај link dо оvе stаvkе:
https://open.uns.ac.rs/handle/123456789/8231
Nаziv: | Temporal discrete cosine transform for speech emotion recognition | Аutоri: | Popović, Branislav Stanković, Igor Ostrogonac, Stevan |
Dаtum izdаvаnjа: | 1-јан-2013 | Čаsоpis: | 4th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2013 - Proceedings | Sažetak: | Temporal Discrete Cosine Transform (TDCT) features have shown good performance in the speaker verification task, and in this paper we utilize them in speech emotion recognition. Tests were conducted on a Serbian emotional speech database, using Neural Networks (NN) as a classifier and Mel-Frequency Cepstral Coefficients (MFFC) as a reference feature set. Even though MFCC is one of the most employed techniques in emotion recognition, our results show that the TDCT features outperform MFCCs (with the first and second derivation) with any number of hidden nodes in the network, hence proving as an excellent starting feature set for recognizing emotions in South Slavic languages. © 2013 IEEE. | URI: | https://open.uns.ac.rs/handle/123456789/8231 | ISBN: | 9781479915439 | DOI: | 10.1109/CogInfoCom.2013.6719219 |
Nаlаzi sе u kоlеkciјаmа: | FTN Publikacije/Publications |
Prikаzаti cеlоkupаn zаpis stаvki
SCOPUSTM
Nаvоđеnjа
3
prоvеrеnо 10.05.2024.
Prеglеd/i stаnicа
16
Prоtеklа nеdеljа
9
9
Prоtеkli mеsеc
0
0
prоvеrеnо 03.05.2024.
Google ScholarTM
Prоvеritе
Аlt mеtrikа
Stаvkе nа DSpace-u su zаštićеnе аutоrskim prаvimа, sа svim prаvimа zаdržаnim, оsim аkо nije drugačije naznačeno.