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dc.contributor.author Park, Young-Jin -
dc.contributor.author Cho, Hui-Sup -
dc.date.accessioned 2021-01-29T07:28:05Z -
dc.date.available 2021-01-29T07:28:05Z -
dc.date.created 2021-01-14 -
dc.date.issued 2020-11-03 -
dc.identifier.isbn 9781728161648 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/12886 -
dc.description.abstract In this study, we conduct a machine learning experiment using the UrbanSound8k dataset to recognize urban sound It can be used in cases where sound cannot be recognized due to a variety of noises through machine learning, and in areas where hearing must be protected, such as worker safety of workers. We extract mel-spectrogram from a sound file dataset and convert it to an image format for learning and validation and then determine the accuracy of the experiment. In the future, the results of our experiment will be used with non-contact sensor information from various devices such as electromagnetic sensors to safeguard workers operating in dangerous areas. © 2020 IEEE. -
dc.language English -
dc.publisher Institute of Electrical and Electronics Engineers Inc. -
dc.title An Experiment of Sound Recognition using Machine Learning -
dc.type Conference Paper -
dc.identifier.doi 10.1109/ICCE-Asia49877.2020.9277368 -
dc.identifier.scopusid 2-s2.0-85098848982 -
dc.identifier.bibliographicCitation 2020 IEEE International Conference on Consumer Electronics - Asia, ICCE-Asia 2020 -
dc.identifier.url http://www.icce-asia2020.org/2020/download/ICCE-Asia_2020_Program_Book_v4.pdf -
dc.citation.conferencePlace KO -
dc.citation.conferencePlace 부산 -
dc.citation.title 2020 IEEE International Conference on Consumer Electronics - Asia, ICCE-Asia 2020 -
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