响度特征量化的改进算法

为提取噪声信号的响度特征,研究Zwicker响度计算模型中安静状况下听阈对应的激励、被计算声音对应的激励和参考声强对应的激励3个参数参与运算的方式,引入等响曲线上24个临界频带中心频率对应的听阈声强级,提出了通过求取噪声信号的能量,计算噪声信号各临界频带的特性响度值的响度计算改进算法。利用这一算法可方便地计算噪声信号不同临界频带的响度值,这些特性响度值可组成一个24维响度特征矢量,以应用于信号分析、模式识别等。通过水声目标的模式识别实验,验证了这一信号响度特征量化改进算法的有效性和实用性。

Improved Algorithm of Quantificational Loudness Feature

Three parameters of Zwicker''s loudness model, the excitation at threshold in quiet, the excitation that corresponds to the test signal and the reference intensity are researched in order to extract the loudness feature of signals. The sound intensity level at threshold in quiet state is introduced, corresponding to the centre frequency of the 24 critical-bands in equal-loudness contours. Then, an improved algorithm based on Zwicker''s loudness model is put forward, with which the specific loudness values can be calculated quantitatively by using the energy of signals. Then a 24-D loudness characteristic vector is composed of the specific loudness values of the critical-bands, which can be used for signal analysis, mode classification and so on. The mode classification experiment of underwater targets is performed. The result shows that the improved algorithm based on Zwicker''s loudness model is effective and practicable.