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    ARTICLE

    Profiling of Urban Noise Using Artificial Intelligence

    Le Quang Thao1,2,*, Duong Duc Cuong2, Tran Thi Tuong Anh3, Tran Duc Luong4

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1309-1321, 2023, DOI:10.32604/csse.2023.031010

    Abstract Noise pollution tends to receive less awareness compared to other types of pollution, however, it greatly impacts the quality of life for humans such as causing sleep disruption, stress or hearing impairment. Profiling urban sound through the identification of noise sources in cities could help to benefit livability by reducing exposure to noise pollution through methods such as noise control, planning of the soundscape environment, or selection of safe living space. In this paper, we proposed a self-attention long short-term memory (LSTM) method that can improve sound classification compared to previous baselines. An attention mechanism will be designed solely to… More >

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