Deep Neural Networks for Road Surface Roughness Classification from Acoustic Signals

Ambrosini L, Gabrielli L, Vesperini F, Squartini S, Cattani L. Deep Neural Networks for Road Surface Roughness Classification from Acoustic Signals. In: AES Convention 144. Audio Engineering Society; 2018. Paper 9934. Available from: https://aes.org/publications/elibrary-page/?id=19451

@inproceedings{Ambrosini2018_19451,
  author = {Ambrosini, Livio and Gabrielli, Leonardo and Vesperini, Fabio and Squartini, Stefano and Cattani, Luca},
  title = {{Deep Neural Networks for Road Surface Roughness Classification from Acoustic Signals}},
  booktitle = {AES Convention 144},
  note = {Paper 9934},
  year = {2018},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=19451}
}

TY  - CPAPER
TI  - Deep Neural Networks for Road Surface Roughness Classification from Acoustic Signals
AU  - Ambrosini, Livio
AU  - Gabrielli, Leonardo
AU  - Vesperini, Fabio
AU  - Squartini, Stefano
AU  - Cattani, Luca
T2  - AES Convention 144
M1  - Paper 9934
PY  - 2018
DA  - 2018/05/06
UR  - https://aes.org/publications/elibrary-page/?id=19451
PB  - Audio Engineering Society
LA  - en
AB  - Vehicle noise emissions are highly dependent on the road surface roughness and materials. A classification of the road surface conditions may be useful in several regards, from driving assistance to in-car audio equalization. With the present work we exploit deep neural networks for the classification of the road surface roughness using microphones placed inside and outside the vehicle. A database is built to test our classification algorithms and results are reported, showing that the roughness classification is feasible with the proposed approach.
ER  -