| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Applied Acoustics | ||
| Dergi ISSN | 0003-682X Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 03-2019 |
| Cilt / Sayı / Sayfa | 146 / 1 / 320–326 | DOI | 10.1016/j.apacoust.2018.11.028 |
| Makale Linki | https://linkinghub.elsevier.com/retrieve/pii/S0003682X18309915 | ||
| Özet |
| Speech emotion recognition involves analyzing vocal changes caused by emotions with acoustic analysis and determining the features to be used for emotion recognition. The number of features obtained by acoustic analysis reaches very high values depending on the number of acoustic parameters used and statistical variations of these parameters. Not all of these features are effective for emotion recognition; in addition, different emotions may effect different vocal features. For this reason, feature selection methods are used to increase the emotional recognition success and reduce workload with fewer features. There is no certainty that existing feature selection methods increase/decrease emotion recognition success; some of these methods increase the total workload. In this study, a new statistical feature selection method is proposed based on the changes in emotions on acoustic features. The success of the … |
| Anahtar Kelimeler |
| Emotion recognition | Feature selection | Speech emotion recognition | Speech processing |
| Atıf Sayıları | |
| Google Scholar | 221 |
| Scopus | 63 |
| Dergi Adı | APPLIED ACOUSTICS |
| Yayıncı | Elsevier Ltd |
| Açık Erişim | Hayır |
| ISSN | 0003-682X |
| E-ISSN | 1872-910X |
| CiteScore | 7,4 |
| SJR | 0,956 |
| SNIP | 1,520 |