Auditive identification of signal-processed environmental sounds: Monitoring the environment

Abstract

The goal of the present study was to compare six transposing signal-processing algorithms based on different principles (Fourier-based and modulation based), and to choose the algorithm that best enables identification of environmental sounds, i.e. improves the ability to monitor events in the surroundings. Ten children (12–15 years) and 10 adults (21–33 years) with normal hearing listened to 45 representative environmental (events) sounds processed using the six algorithms, and identified them in three different listening experiments involving an increasing degree of experience. The sounds were selected based on their importance for normal hearing and deaf-blind subjects. Results showed that the algorithm based on transposition of 1/3 octaves (fixed frequencies) with large bandwidth was better (p<0.015) than algorithms based on modulation. There was also a significant effect of experience (p<0.001). Adults were significantly (p<0.05) better than children for two algorithms. No clear gender difference was observed. It is concluded that the algorithm based on transposition with large bandwidth and fixed frequencies is the most promising for development of hearing aids to monitor environmental sounds.