Low-power implementation of an HMM-based sound environment classification algorithm for hearing aid application

Automatic program switching is a future trend for digital hearing aids. To realize this function, a solution for sound environment classification is required. This paper presents an HMM-based sound environment classifier that is implemented on a low-power DSP system designed for hearing aid applications. Our experimental results show that it is capable of distinguishing four sound sources (i.e. speech, music, car noise, and babble) with more than 95% accuracy rate and consumes only 0.225 mW of power.