To avoid failures in the marketplace, the control of the risks in product innovation and the reduction of the innovation cycles require fast and valid assessments from customers. An interactive genetic algorithm (IGA) is proposed for eliciting users' perceptions about the shape of a product, in order to stimulate creativity and to identify design trends. Interactive users' assessment tests are conducted on virtual products to capture and analyze users' responses. The IGA is interfaced with Computer Aided Design (CAD) software (CATIA V5) to create sets of parameterized designs in real time, which are presented iteratively by a graphical interface to the users for evaluation. After a description of the IGA, a study on the convergence of the IGA is presented. The convergence varies, according to the tuning parameters of the algorithm and the size of the design problem. An experiment was carried out with a set of 45 users on the application case, a dashboard, put forward by Renault. The implementation of the perceptive tests and the analysis of the results are described using hierarchical ascendant classification (HAC) and multivariate analysis. This paper shows how the results of tests using IGA can be used to elicit user perception and to detect design trends.
This study focuses on a particular attribute of trumpet tones, the brightness, and on the physical characteristics of the instrument thought to govern its magnitude. On the one hand, an objective study was carried out with input impedance measurements, and, on the other hand, a subjective study with hearing tests and a panel of subjects. To create a set of different trumpets a variable depth mouthpiece was developed whose depth can be easily and continuously adjusted from "deep" to "shallow." Using this mouthpiece and the same trumpet, several instruments were generated which may be played in three ways: (i) by a musician, (ii) by an artificial mouth, and (iii) using physical modeling simulations. The influence of the depth of the mouthpiece on the perception of the trumpet's tones was investigated, and the ability of a musician, the artificial mouth, or physical modeling simulations to demonstrate perceptively noticeable differences was assessed. Physical characteristics extracted from the impedance curves are finally proposed to explain the brightness of trumpet tones. As a result, the physical modeling simulations now seem to be mature enough to exhibit coherent and subtle perceptual differences between tones. This opens the door to virtual acoustics for instrument makers.
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