Musical-Inspired Features for Automatic Sound Classification in Digital Hearing Aids

Alexandre E, Canadas-Quesada FJ, Rosa-Zurera M, Ruiz-Reyes N, Vera-Candeas P. Musical-Inspired Features for Automatic Sound Classification in Digital Hearing Aids. In: AES Convention 124. Audio Engineering Society; 2008. Paper 7435. Available from: https://aes.org/publications/elibrary-page/?id=14565

@inproceedings{Alexandre2008_14565,
  author = {Alexandre, Enrique and Canadas-Quesada, Francisco Jesus and Rosa-Zurera, Manuel and Ruiz-Reyes, Nicolas and Vera-Candeas, Pedro},
  title = {{Musical-Inspired Features for Automatic Sound Classification in Digital Hearing Aids}},
  booktitle = {AES Convention 124},
  note = {Paper 7435},
  year = {2008},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=14565}
}

TY  - CPAPER
TI  - Musical-Inspired Features for Automatic Sound Classification in Digital Hearing Aids
AU  - Alexandre, Enrique
AU  - Canadas-Quesada, Francisco Jesus
AU  - Rosa-Zurera, Manuel
AU  - Ruiz-Reyes, Nicolas
AU  - Vera-Candeas, Pedro
T2  - AES Convention 124
M1  - Paper 7435
PY  - 2008
DA  - 2008/05/06
UR  - https://aes.org/publications/elibrary-page/?id=14565
PB  - Audio Engineering Society
LA  - en
AB  - This paper proposes the use of some musical-inspired features for the automatic classification of sounds in digital hearing aids. This kind of application is characterized by very strong constraints in terms of computational complexity. The proposed features are based on fundamental frequency detection and exhibit a low computational complexity while providing good results in terms of probability of correct classification. The performance of the system will be tested using an 1-NN classifier being the goal to distinguish among speech, noise and music. For the experiments, a sound database, obtained using a hearing aid simulator, will be used.
ER  -