Abstract
The field of study interested in the development of computer algorithm for transforming data into intelligent actions is known as machine learning. The paper investigates different machine learning classification algorithms and their effectiveness in environmental sound recognition. Efforts are made in selecting the suitable audio feature extraction technique and finding a direct connection between audio feature extraction technique and the quality of the algorithm performance. These techniques are compared to determine the most suitable for solving the problem of environmental sound recognition.
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Jekic, N., Pester, A. (2019). Environmental Sound Recognition with Classical Machine Learning Algorithms. In: Auer, M., Langmann, R. (eds) Smart Industry & Smart Education. REV 2018. Lecture Notes in Networks and Systems, vol 47. Springer, Cham. https://doi.org/10.1007/978-3-319-95678-7_2
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DOI: https://doi.org/10.1007/978-3-319-95678-7_2
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-95677-0
Online ISBN: 978-3-319-95678-7
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