Ray W. Herrick Labs., School of Mech. Eng., Purdue Univ., West Lafayette, IN 47907-1077
Loudness, percentile loudness, sharpness, and fluctuation strength have been shown in laboratory experiments to be correlated with annoyance. Zwicker proposed a model of unbiased annoyance (UBA) based on time of day (d), fluctuation strength (F), sharpness (S), and N[sub 10]. In psychoacoustic tests on amplitude-modulated noise signals [P. Laux and P. Davies, NCEJ 40 (3) (May-June 1993)] UBA has been shown to have a higher correlation to annoyance than other commonly used noise measures, although, other correlation models were found to produce an even better model of the relationship between (S,N[sub 10],F) and the subjective ratings. The use of artificial neural networks (ANNs) to describe the relationship between (S,N[sub 10],F) and the subjective responses has been investigated. The smaller the network, the fewer the number of weights, and the fewer the number of signals that a subject has to rate. The objective of the research was to estimate a network that was the smallest possible model of the data. As a starting point UBA was modeled as a function of (S,N[sub 10],F); the resulting ANN model of UBA was then used as the initial conditions when subjective data were available.