TY - GEN
T1 - Detection of boat noise by a convolutional neural network for a boat information system
AU - Yamaguchi, Haruki
AU - Muto, Kenji
N1 - Publisher Copyright:
© 2019 Proceedings of the International Congress on Acoustics. All rights reserved.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2019
Y1 - 2019
N2 - Some boat noises are perceived as noisy and annoying by people who live near canals. We have previously proposed an information system that uses audiovisual means to provide cellphone alerts of approaching noisy boats, but a problem with that system was camera-based detection of a boat approaching at night. In the present paper, we investigate using training data to detect boat noise in environmental sound by means of a convolutional neural network. To detect boat noise, training data are used involving spectrograms of the environmental sound. The spectrogram configuration is investigated to improve the detection of boat noise. From the results, when the spectrogram configuration has a time axis of 5 s and a frequency axis of 10-3,500 Hz, the detection performance has a highest accuracy of over 95%.
AB - Some boat noises are perceived as noisy and annoying by people who live near canals. We have previously proposed an information system that uses audiovisual means to provide cellphone alerts of approaching noisy boats, but a problem with that system was camera-based detection of a boat approaching at night. In the present paper, we investigate using training data to detect boat noise in environmental sound by means of a convolutional neural network. To detect boat noise, training data are used involving spectrograms of the environmental sound. The spectrogram configuration is investigated to improve the detection of boat noise. From the results, when the spectrogram configuration has a time axis of 5 s and a frequency axis of 10-3,500 Hz, the detection performance has a highest accuracy of over 95%.
KW - Boat noise
KW - Convolutional neural network
KW - Noise detection
KW - Sound recognition
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U2 - 10.18154/RWTH-CONV-239082
DO - 10.18154/RWTH-CONV-239082
M3 - Conference contribution
AN - SCOPUS:85099330232
T3 - Proceedings of the International Congress on Acoustics
SP - 2848
EP - 2853
BT - Proceedings of the 23rd International Congress on Acoustics
A2 - Ochmann, Martin
A2 - Michael, Vorlander
A2 - Fels, Janina
PB - International Commission for Acoustics (ICA)
T2 - 23rd International Congress on Acoustics: Integrating 4th EAA Euroregio, ICA 2019
Y2 - 9 September 2019 through 23 September 2019
ER -