| Popis: |
Sound quality evaluation may be conducted with multiple different objective evaluation models, but reliability of evaluation results is different. Noise samples of two ears of the driver were gathered when the car operated at the speed of 60km/h and different music was played in the car. After equal loudness, frequency band and filtering treatment of sound samples, subjective evaluation of sound quality was carried out. Based on calculation of objective parameters, MLR (Multiple Linear Regression) objective evaluation model for sound quality, objective evaluation model for sound quality based on BP neural network and objective evaluation model for sound quality based on RBF (radial basis function) neural network were established. The test samples were substitute into the three models, and their sound quality prediction effects at each frequency band were compared. The results show that MLR model is simple and has fast calculation speed, so it is suitable for linear problem analysis; BP neural network model is suitable for solving large sample problem with complex internal mechanism; RBF neural network model has high precision and small relative error, so it is suitable for analysis of nonlinear problem of small sample. Under experimental conditions, prediction effect of RBF model is superior to MLR model and BP neural network model. |
