On the Design of Automatic Sound Classification Systems for Digital Hearing Aids
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.
Click to purchase paper or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members, $5 for AES members and is free for E-Library subscribers.