A hybrid CNN-LSTM model for environmental sound classification: Leveraging feature engineering and transfer learning

Environmental Sound Classification (ESC) remains a significant challenge due to the dynamic nature of audio data, scarcity of labeled datasets, and the complexity of feature extraction. Existing deep learning approaches, such as CNNs and RNNs, frequently struggle to manage diverse sound features, ac...

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Veröffentlicht in:	Digital signal processing Jg. 163; S. 105234
Hauptverfasser:	Akter, Rubaiya, Islam, Md. Rezwanul, Debnath, Sumon Kumar, Sarker, Prodip Kumar, Uddin, Md. Kamal
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.08.2025
Schlagworte:	Deep learning Environmental sound classification Evaluation metrics Hybrid model Mel-frequency cepstral coefficients Deep learning Mel-frequency cepstral coefficients Hybrid model Environmental sound classification Evaluation metrics
ISSN:	1051-2004
Online-Zugang:	Volltext
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