Smart City Gnosys

Smart city article details

Title	Deep Learning Methods For Audio Events Detection
ID_Doc	17908
Authors	Ciaburro G.
Year	2021
Published	Studies in Big Data, 82
DOI	http://dx.doi.org/10.1007/978-981-15-9492-2_8
Abstract	Deep learning is a branch of machine learning that is based on the use of algorithms whose purpose is the modeling of high-level abstractions on data. It is part of a family of targeted techniques learning methods to represent data. Convolutional neural networks (CNN) represent a type of neural network in which the connection pattern between neurons is inspired by the structure of the visual cortex in the animal world. The individual neurons present in this part of the brain respond to certain stimuli in a restricted region of observation, called the receptive field. CNNs are designed to recognize visual patterns directly in images represented by pixels and require a preprocessing quantity that is zero or very limited. They can recognize extremely variable patterns, such as freehand writing and images representing the real world. Typically, a CNN consists of several alternating layers of convolution and pooling followed by one or more final levels fully connected in the case of classification, or by a certain number of levels of upsampling in the regression case. In this chapter, we will see how to identify audio events in a complex sound scenario using convolutional neural networks. An automatic identification system for sound events can prove extremely useful in different contexts: safety of public events, home acoustic monitoring, bioacoustics monitoring, acoustic monitoring for healthcare, and more generally for the needs of smart cities. The variability of sound events determines continuous changes in frequency content that can hardly be traced with the instruments commonly used in traditional acoustics. Convolutional neural networks (CNN) are useful for learning the shift-invariant filters that are essential for modeling audio events. © 2021, Springer Nature Singapore Pte Ltd.
Author Keywords	Artificial intelligence; Audio events detection; Convolutional neural networks; Data mining; Deep learning; Machine learning; Mel-frequency cepstral coefficients; Pattern recognition; Sounds classification; Spectral signature

Similar Articles

Id	Similarity	Authors	Title	Published
8076	0.912	Mukhamadiyev A.; Khujayarov I.; Nabieva D.; Cho J.	An Ensemble Of Convolutional Neural Networks For Sound Event Detection	Mathematics, 13, 9 (2025)
59656	0.893	Hidayat A.; Njoo D.B.P.; Adrian G.D.; Setyoko D.E.; Wijanarko B.D.	Unlocking Soundscapes: Harnessing Machine Learning For Sound Classification	Proceeding of 2024 9th International Conference on Information Technology and Digital Applications, ICITDA 2024 (2024)
14305	0.881	Agarwal M.; Gill K.S.; Chattopadhyay S.; Singh M.	Classification Of Urban Sound Using Sequential Convolutional Neural Network (Cnn) Model And Its Visualisation	2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems, ICITEICS 2024 (2024)
19236	0.881	Hattaraki S.M.; Kambalimath S.G.; Savukar B.P.; Bagali S.; Dixit U.D.; Jadhav A.S.	Detection And Classification Of Various Listening Environments For Hearing-Impaired Individuals Using Crnn	2024 International Conference on Innovation and Novelty in Engineering and Technology, INNOVA 2024 - Proceedings (2024)
60186	0.876	Agarwal M.; Gill K.S.; Aggarwal P.; Rawat R.S.; Sunil G.	Urban Sound Classification Using Vgg19 Convolutional Neural Network (Cnn) Model And Its Visualisation	4th International Conference on Innovative Practices in Technology and Management 2024, ICIPTM 2024 (2024)
11080	0.875	Golovnin O.; Privalov A.; Stolbova A.; Ivaschenko A.	Audio-Based Vehicle Detection Implementing Artificial Intelligence	Studies in Systems, Decision and Control, 337 (2021)
60187	0.871	Lakshmi R.; Chaitra N.C.; Thejaswini R.; Swapna H.; Parameshachari B.D.; Kumar S.D.S.; Puttegowda K.	Urban Sound Classification With Convolutional Neural Network	2nd IEEE International Conference on Integrated Intelligence and Communication Systems, ICIICS 2024 (2024)
17834	0.869	Sungeetha D.; Nanthini S.; Sivabalan R.; Soundari A.G.; Legapriyadharshini N.; Rajaram G.	Deep Learning Based Detection And Delineation Sound In Smart City System	8th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2024 - Proceedings (2024)
14555	0.866	Seker H.; Inik O.	Cnnsound: Convolutional Neural Networks For The Classification Of Environmental Sounds	ACM International Conference Proceeding Series (2020)
38435	0.858	Chen T.-S.; Chen M.-J.; Chen T.-C.	Multi-Task Deep Learning Approach For Sound Event Recognition And Tracking	International Journal of Ad Hoc and Ubiquitous Computing, 46, 2 (2024)