Starter's pistols are often bought for self-defense, but can also be used for criminal activities (e.g. assaults, etc.). When a starter's pistol is loaded with blank cartridges and is fired, a powerful shooting noise results. The level of the noise produced is high enough to cause acoustic trauma. For legal examinations and giving an expert opinion further information is needed about the power of such noise. We examined how high peak sound pressure levels were of the gunshots of blank cartridges and whether there existed any directional characteristics from the noise emissions. In all, 15 different models of starter's pistols of 8 different calibres were examined. In addition to blank cartridges, 8 mm tear gas cartridges were also examined. Four transducers were situated in the horizontal plane around the muzzle: 0 degree (shooting direction), 45 degrees, 90 degrees, and 180 degrees (towards the firer). The distances between the transducers and the muzzle were 25 cm, 50 cm, 100 cm, and 200 cm. At a distance of 1 m and in the 0 degree shooting direction the peak sound pressure levels of nearly all weapons tested exceeded 160 dB. At a shooting distance of 25 cm the peak sound pressure levels reached 181 dB. In addition, we observed a directional characteristic concerning the emission of noise: pistols produced higher peak sound pressure levels to the front than backwards towards the firer.

The sound quality of products is often evaluated in hearing experiments using the semantic differential and a subsequent factorial analysis. In this study the method is applied to determine basic hearing properties. In order to achieve optimal results of the hearing experiment, special interest has been taken in the choice of adjectives and sounds. This selection is based on the results of a previously conducted survey of sound attributes. The selected 25 sounds were recorded using an artificial head and presented binaurally to a jury of 20 adults with normal hearing. A factorial analysis of the ratings on 24 attribute scales produced six factors representing basic perceptive cognitive and emotional hearing dimensions. In a last step connections between these dimensions and psychoacoustical parameters calculated from the sounds were evaluated using an analysis of correlation. Although the results show high correlations between loudness, sharpness, and pitch strength and equivalent attributes, no such connections could be found for the psychoacoustical roughness and fluctuation strength. In order to find better-correlated parameters, other calculation methods for these properties are investigated.

The current noise control methods are not sufficient for covering the ratings of different kinds of noise. They are mainly based on experiments with stationary and artificial test signals. New judgment models have to be developed to account for the time fluctuations of environmental sounds. During the last decade algorithms emerged in connectionism that not only find optimal mappings within stationary data (for example the backpropagation algorithm) but also within time series. One architecture for this task is called finite impulse response (FIR) neural network. Due to the architecture the networks include preceding time steps for the calculation of the current output. This contribution presents FIR neural networks to model sound quality judgments on environmental sounds. A listening test has been conducted for collecting training samples for the network and for testing its generalization abilities. The sound patterns and the subjects answers are pre-processed using factor analysis. The analysis of the subjects answers yielded 2 factors, which can be identified to represent the sound attributes annoying and powerful. The FIR neural networks are trained to estimate both attributes. The results of training and generalization show high correlation between the sound attributes and predicted judgments of the neural networks.

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