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Impression Evaluation Model for Button Sounds Using a Neural Network
This paper presents an impression evaluation model for button sounds generated when users press the buttons on car audio equipment using a neural network. The dynamic characteristics of 11 kinds of button sounds obtained by their wavelet transform frequencies and sound pressure values are fed into the network model inputs. The model then responds with three factor scores, “esthetic”, “force” and “metallic”, and an evaluation value of “offensive - pleasant” as the outputs. By analyzing the inside functions of the neural network after training, we confirmed the model acquired a mechanism that extracted four impression evaluation values from the sound characteristics, thus showing the model could attain automation of button sound design.
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