Investigation of the effectiveness of time-frequency domain images and acoustic features in urban sound classification
Yazarlar (1)
Prof. Dr. Turgut ÖZSEVEN Tokat Gaziosmanpaşa Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Applied Acoustics (Q1) | ||
| Dergi ISSN | 0003-682X Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 08-2023 |
| Cilt / Sayı / Sayfa | 211 / 1 / 1–10 | DOI | 10.1016/j.apacoust.2023.109564 |
| Makale Linki | http://dx.doi.org/10.1016/j.apacoust.2023.109564 | ||
| Özet |
| Rapid urbanization and population growth worldwide seriously challenge building livable and sustainable cities. This increase causes the increase and diversification of urban sounds. They were transforming these sounds into information instead of just being heard, as noise plays an important role in the concept of smart cities. For this purpose, two basic methods are used to classify urban sounds. In the first of these, the sounds are processed by signal processing methods, and handcrafted features are obtained. In the other method, sounds are represented visually and classified with deep learning models. This study investigated the effect of the individual and hybrid use of features used in both approaches on the classification of urban sounds. In addition, a CNN model was created to classify hybrid features. The results obtained showed that both approaches produced successful results in classification. Among … |
| Anahtar Kelimeler |
| Acoustic analysis | Audio-visual feature set | Cepstral features | Deep learning | Environmental sound classification | Smart city | Sound event recognition | Urban sound recognition |
Science Direct
Investigation of the effectiveness of time-frequency domain images and acoustic features in urban sound classification
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 19 |
| Scopus | 15 |