CONCLUDING REMARKS

Abstract

The choice of problems presented in this study is intended to emphasize that in some cases even the classical problems of acoustics can be addressed and solved by means of new methods, especially those arising from the soft computing domain. Before soft computing methods were introduced, all applications dealing with uncertainty were based on the probabilistic approach. Meanwhile, in the case of some of the studied applications, such as automatic recognition of musical phrases, it is impossible to base the research on such an approach only, because each musical phrase has its unique character that cannot be sufficiently described by any statistics. Similarly, the statistical processing of subjective testing results is not fully reliable in most practical applications in which relatively small data sets are available. Moreover, the hitherto used statistical analyses do not allow for directly formulating rules showing the relations between assessed parameters. Such rules are needed to analyze the acoustical phenomena underlying the preference of subjective quality of sound. In the above mentioned applications a rule-based decision systems are necessary to ensure a more accurate data analysis and a better understanding of the phenomena under scrutiny on the basis of obtained results.