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E. Alexandre, L. Álvarez-Perez, R. Gil-Pita, R. Vicen-Bueno, and L. Cuadra, "On the Design of Automatic Sound Classification Systems for Digital Hearing Aids," Paper 7735, (2009 May.). doi: E. Alexandre, L. Álvarez-Perez, R. Gil-Pita, R. Vicen-Bueno, and L. Cuadra, "On the Design of Automatic Sound Classification Systems for Digital Hearing Aids," Paper 7735, (2009 May.). doi:
Abstract: The design of digital hearing aids able to carry out advanced functionalities (such as, for instance, classify the acoustic environment and automatically select the best amplification program for the user's comfort) exhibits a great difficulty. Since hearing aids have to work at very low clock frequency in order to minimize power consumption and maximize life battery, the number of available instructions per second is actually very small. This enforces to design efficient algorithms with a reduced number of instructions. In particular, the paper will focus on three extremely related topics: 1) The design of low-complexity features; 2) The use of automatic feature selection algorithms to optimize the performance of the classifier; and 3) The critical analysis of a variety of different classification algorithms, basically based on their complexity and performance, and determining whether o not they are feasible to be implemented.

@article{alexandre2009on,
author={alexandre, enrique and álvarez-perez, lorena and gil-pita, roberto and vicen-bueno, raúl and cuadra, lucas},
journal={journal of the audio engineering society},
title={on the design of automatic sound classification systems for digital hearing aids},
year={2009},
volume={},
number={},
pages={},
doi={},
month={may},} @article{alexandre2009on,
author={alexandre, enrique and álvarez-perez, lorena and gil-pita, roberto and vicen-bueno, raúl and cuadra, lucas},
journal={journal of the audio engineering society},
title={on the design of automatic sound classification systems for digital hearing aids},
year={2009},
volume={},
number={},
pages={},
doi={},
month={may},
abstract={the design of digital hearing aids able to carry out advanced functionalities (such as, for instance, classify the acoustic environment and automatically select the best amplification program for the user's comfort) exhibits a great difficulty. since hearing aids have to work at very low clock frequency in order to minimize power consumption and maximize life battery, the number of available instructions per second is actually very small. this enforces to design efficient algorithms with a reduced number of instructions. in particular, the paper will focus on three extremely related topics: 1) the design of low-complexity features; 2) the use of automatic feature selection algorithms to optimize the performance of the classifier; and 3) the critical analysis of a variety of different classification algorithms, basically based on their complexity and performance, and determining whether o not they are feasible to be implemented.},}

TY - paper
TI - On the Design of Automatic Sound Classification Systems for Digital Hearing Aids
SP - EP -
AU - Alexandre, Enrique
AU - Álvarez-Perez, Lorena
AU - Gil-Pita, Roberto
AU - Vicen-Bueno, Raúl
AU - Cuadra, Lucas
PY - 2009
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2009 TY - paper
TI - On the Design of Automatic Sound Classification Systems for Digital Hearing Aids
SP - EP -
AU - Alexandre, Enrique
AU - Álvarez-Perez, Lorena
AU - Gil-Pita, Roberto
AU - Vicen-Bueno, Raúl
AU - Cuadra, Lucas
PY - 2009
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2009
AB - The design of digital hearing aids able to carry out advanced functionalities (such as, for instance, classify the acoustic environment and automatically select the best amplification program for the user's comfort) exhibits a great difficulty. Since hearing aids have to work at very low clock frequency in order to minimize power consumption and maximize life battery, the number of available instructions per second is actually very small. This enforces to design efficient algorithms with a reduced number of instructions. In particular, the paper will focus on three extremely related topics: 1) The design of low-complexity features; 2) The use of automatic feature selection algorithms to optimize the performance of the classifier; and 3) The critical analysis of a variety of different classification algorithms, basically based on their complexity and performance, and determining whether o not they are feasible to be implemented.