| Summary: | 碩士 === 南台科技大學 === 多媒體與電腦娛樂科學系 === 101 === Digital game industry in recent years, the rapid growth of output, from the early family computer until now the next generation of games, not only gaming platform, more and more players for the game screen, shot in more and more stress. In order to grasp the market as well as the player's first impression, most of the games industry are almost always focused on the center of gravity "planning", "art" and "programs" in three points. In addition to music type of game, there are few operators to focus on the "musical sound" on. Therefore, this study selected sound theme game sound and explore the emotional response relationship between players and connected, and its main purpose can be summarized as the following three points: （1）the affective gaming audio category labels; （2）game sound the emotional response categories; （3）game sound design reference.
In this study, Kansei Engineering as a starting point, the first preliminary study to identify representative game type, and then type audio for gaming and sound emotional vocabulary sample collection filter, and finally sorting through factor analysis and the use of labels to establish an emotional support vector machine classification model . The results show that emotional reactions classify the results of three sets of scales classification labels are "emotional sensitivity", "suggestive" and "variability" and category labels for these three groups, respectively, for audio analysis, we can see that each segment label and volume, timbre and tone that characterized the relationship between the three voices. Eventually, by the support vector machine have obtained the best training model average accuracy rate was 94.4%, indicating that the results of the feasibility study. And if the designer for these indicators to be refined, but will also make sound reaches the emotional needs and matching games.
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