Application of Rough Set on Extraction of Sound Quality Parameters

As the most important objective parameters, reverberation time and clarity play significant roles in acoustic field characteristics evaluation of the hall. The discrepancies of influences among scene image feature parameters on different timbre parameter have been dug out through attribute reduction of rough-set theory. The minimum decision-making algorithm is processed by mining decision-making rules from the scene image data. It can reckon the approximate range of reverberation time and clarity. Finally the validity of the model is proved through the experiment results of model training on the test data. It provides a brand-new idea for virtual reality technique and sound quality evaluation of virtual environment with using this method.