On the Meaning of Noise Annoyance Modifiers: A Fuzzy Set Theoretical Approach

This paper reports on a fuzzy analysis of information gathered by many colleagues on the precise meaning of noise annoyance modifiers in 9 different languages. It is shown how fuzzy set theory can help us to construct a mathematical background for translating these modifiers between the languages concerned. A second goal of annoyance modifier research is to define labels to be used in noise annoyance surveys in order to obtain accurate and comparable results. Similarity measures used to compare fuzzy sets associated with verbal descriptors of annoyance levels indicate to what extent previously proposed labels [1] match between the languages considered. An ideal language from the fuzzy point of view where a continuous annoyance scale is exactly divided into n equal parts is translated to these natural languages and results in an alternative selection of labels that are better suited for fuzzy calculus. In general this selection of labels corresponds quite well with the set proposed in [1] which is rather surprising since the fuzzy set approach lacks most of the human input used in the ICBEN selection procedure.