| Summary: | 碩士 === 國立交通大學 === 工學院聲音與音樂創意科技碩士學位學程 === 99 === The reason for the general appeal of music lies in the emotional feedback that music offers to its listeners. So, how to extract an effective approach from music signal to identify emotions response is the main purpose. This work proposes that music arouse our emotion response turn to the next story with continuous playback, it should be a real-time alteration not a static state. For the reason, research proposes a sequential framework real-time system to tracking emotions evoked by musical signals and recording the rate of each mood total time length. The higher proportion of mood means listeners feeling are more strong and long-term. The research considers psychological factors and cites Thayer's mood model reference. Five feature sets are extracted from the 200 WAV file music clips labeled mood state and applying to「Emotion Scores Counting」to define the distribution of sample space. Next, training two classifier (GMM, BPN) and recognize emotion by 100 Pop music testing data. Finally, the system has three methods (static emotion tracking, time-lasted rate and dynamic emotion locus visualization) to exhibit our result. Beside the researchers invite 66 college students attending total of five times music mood questionnaire survey to statistics an objective result as research verification.
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