Analysis of methods and approaches for sound event detection in emergency situations

Набиева, Д.Т., Юлдашева, У.Х.

Рақамли технологияларнинг назарий ва амалий масалалари · 2026-yil

Annotatsiya

This paper presents a comprehensive review of existing methods and approaches for Sound Event Detection (SED) in environmental acoustic monitoring. The theoretical foundations of SED, acoustic feature extraction techniques (MFCC, Mel-spectrogram, DCT-spectrogram, and cochleogram), traditional machine learning methods (GMM, HMM, and SVM), and modern deep learning architectures (CNN, RNN/LSTM, CRNN, and Transformer) are comprehensively analyzed. The review shows that between 2000 and 2012, manually engineered features combined with conventional machine learning methods achieved detection accuracies of 65–75%, whereas deep learning approaches introduced after 2012 increased performance to 85–96%. In particular, Convolutional Recurrent Neural Networks (CRNNs) achieve accuracies exceeding 90% by effectively modeling local spectral patterns and temporal dependencies while benefiting from ensemble learning techniques. The paper also analyzes widely used benchmark datasets (ESC-50, UrbanSound8K, AudioSet, and FSD50K) and highlights the need for developing specialized datasets for emergency sound detection in residential environments. Furthermore, practical challenges such as noise robustness, real-time inference, and edge computing are discussed, together with promising research directions including Transformer-based architectures, self-supervised learning, and multimodal fusion. The presented review provides a valuable reference for researchers and practitioners working in the field of sound event detection.

Maqola ma’lumotlari
MualliflarНабиева, Д.Т., Юлдашева, У.Х.
JurnalРақамли технологияларнинг назарий ва амалий масалалари
NashriyotТАТУ Самарқанд филиали
ISSN2181-3086, 2181-3094
Nashr sanasi2026-08-02
Jild9
Son3
Betlar53-74
TilIngliz
Ilmiy sohaTexnika
DOI10.62132/ijdt.v9i3.398
Indeksga qo‘shilgan2026-08-26

DOI: 10.62132/ijdt.v9i3.398 · Maqolaning asl sahifasi

Kalit so‘zlar

обнаружение звуковых событий, глубокие нейронные сети, CRNN, акустический мониторинг, умные города, чрезвычайные ситуации, машинное обучение, sound event detection, deep neural networks, CRNN, acoustic monitoring, smart cities, emergency situations, machine learning

Ilmiy soha

Texnika

Iqtibos keltirish

APAНабиева, Д.Т., & Юлдашева, У.Х. (2026). Analysis of methods and approaches for sound event detection in emergency situations. Рақамли технологияларнинг назарий ва амалий масалалари, 9(3), 53-74. https://doi.org/10.62132/ijdt.v9i3.398
GOST (OAK)Набиева, Д.Т., Юлдашева, У.Х. Analysis of methods and approaches for sound event detection in emergency situations // Рақамли технологияларнинг назарий ва амалий масалалари. – 2026. – T. 9, № 3. – P. 53-74. – DOI: 10.62132/ijdt.v9i3.398.
MLAНабиева, Д.Т., and Юлдашева, У.Х. “Analysis of methods and approaches for sound event detection in emergency situations.” Рақамли технологияларнинг назарий ва амалий масалалари, 9(3), 53-74, 2026. https://doi.org/10.62132/ijdt.v9i3.398
ChicagoНабиева, Д.Т., and Юлдашева, У.Х. “Analysis of methods and approaches for sound event detection in emergency situations.” Рақамли технологияларнинг назарий ва амалий масалалари, 9(3), 53-74 (2026). https://doi.org/10.62132/ijdt.v9i3.398
HarvardНабиева, Д.Т., and Юлдашева, У.Х (2026) ‘Analysis of methods and approaches for sound event detection in emergency situations’, Рақамли технологияларнинг назарий ва амалий масалалари, 9(3), 53-74. https://doi.org/10.62132/ijdt.v9i3.398
BibTeX
@article{article2026,
  title = {Analysis of methods and approaches for sound event detection in emergency situations},
  author = {Набиева, Д.Т. and Юлдашева, У.Х.},
  journal = {Рақамли технологияларнинг назарий ва амалий масалалари},
  year = {2026},
  volume = {9},
  number = {3},
  pages = {53-74},
  doi = {10.62132/ijdt.v9i3.398},
  url = {https://doi.org/10.62132/ijdt.v9i3.398}
}

Boshqa maqola uchun iqtibos tayyorlash

Рақамли технологияларнинг назарий ва амалий масалалари jurnalidan boshqa maqolalar

Рақамли технологияларнинг назарий ва амалий масалалари — barcha maqolalar · 2026-yil arxivi

Texnika sohasidagi boshqa maqolalar

Texnika sohasidagi OAK jurnallari