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A model for long-term environmental sound detection

Dick Botteldooren (UGent) and Bert De Coensel (UGent)
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Abstract
In recent years, knowledge on primary processing of sound by the human auditory system has tremendously increased. This paper exploits the opportunities this creates for assessing the impact of (unwanted) environmental noise on quality of life of people. In particular the effect of auditory attention in a multisource context is focused on. The typical application envisaged here is characterized by very long term exposure (days) and multiple listeners (thousands) that need to be assessed. Therefore, the proposed model introduces many simplifications. The results obtained show that the approach is nevertheless capable of generating insight in the emergence of annoyance and the appraisal of open area soundscapes.

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Citation

Please use this url to cite or link to this publication:

MLA
Botteldooren, Dick, and Bert De Coensel. “A Model for Long-Term Environmental Sound Detection.” IEEE International Joint Conference on Neural Networks (IJCNN), IEEE, 2008, pp. 2017–23.
APA
Botteldooren, D., & De Coensel, B. (2008). A model for long-term environmental sound detection. IEEE International Joint Conference on Neural Networks (IJCNN), 2017–2023. New York: IEEE.
Chicago author-date
Botteldooren, Dick, and Bert De Coensel. 2008. “A Model for Long-Term Environmental Sound Detection.” In IEEE International Joint Conference on Neural Networks (IJCNN), 2017–23. New York: IEEE.
Chicago author-date (all authors)
Botteldooren, Dick, and Bert De Coensel. 2008. “A Model for Long-Term Environmental Sound Detection.” In IEEE International Joint Conference on Neural Networks (IJCNN), 2017–2023. New York: IEEE.
Vancouver
1.
Botteldooren D, De Coensel B. A model for long-term environmental sound detection. In: IEEE International Joint Conference on Neural Networks (IJCNN). New York: IEEE; 2008. p. 2017–23.
IEEE
[1]
D. Botteldooren and B. De Coensel, “A model for long-term environmental sound detection,” in IEEE International Joint Conference on Neural Networks (IJCNN), Hong Kong, China, 2008, pp. 2017–2023.
@inproceedings{678894,
  abstract     = {{In recent years, knowledge on primary processing of sound by the human auditory system has tremendously increased. This paper exploits the opportunities this creates for assessing the impact of (unwanted) environmental noise on quality of life of people. In particular the effect of auditory attention in a multisource context is focused on. The typical application envisaged here is characterized by very long term exposure (days) and multiple listeners (thousands) that need to be assessed. Therefore, the proposed model introduces many simplifications. The results obtained show that the approach is nevertheless capable of generating insight in the emergence of annoyance and the appraisal of open area soundscapes.}},
  author       = {{Botteldooren, Dick and De Coensel, Bert}},
  booktitle    = {{IEEE International Joint Conference on Neural Networks (IJCNN)}},
  isbn         = {{978-1-4244-1821-3}},
  issn         = {{1098-7576}},
  language     = {{eng}},
  location     = {{Hong Kong, China}},
  pages        = {{2017--2023}},
  publisher    = {{IEEE}},
  title        = {{A model for long-term environmental sound detection}},
  year         = {{2008}},
}

Web of Science
Times cited: