Ranjbar Parivash, Borg Erik, Philipson Lennart, Stranneby Dag
Department of Technology, Orebro University, Orebro, Sweden.
Int J Audiol. 2008 Dec;47(12):724-36. doi: 10.1080/14992020802289776.
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.
本研究的目的是比较基于不同原理（基于傅里叶变换和基于调制）的六种转换信号处理算法，并选择最能有效识别环境声音的算法，即提高监测周围事件的能力。十名听力正常的儿童（12 - 15岁）和十名成年人（21 - 33岁）聆听了使用这六种算法处理的45种具有代表性的环境（事件）声音，并在涉及经验程度逐渐增加的三个不同听力实验中对其进行识别。这些声音是根据它们对听力正常和聋盲受试者的重要性来选择的。结果表明，基于大带宽1/3倍频程（固定频率）转换的算法比基于调制的算法更好（p<0.015）。经验也有显著影响（p<0.001）。对于两种算法，成年人的表现显著优于儿童（p<0.05）。未观察到明显的性别差异。结论是，基于大带宽和固定频率转换的算法在开发用于监测环境声音的助听器方面最具前景。
