音樂與情緒關係定位之研究

Abstract

本研究目的在於分析古典樂、爵士樂、西洋搖滾樂及流行樂等四種音樂類型共1002首音樂，其訊號組型之間的相關性，並探討訊號組型與情緒的關係，以進行音樂情緒定位。每首音樂的訊號組型透過MDS分析形成二維空間的分佈圖，以座標軸中心點(0,0)區隔為右上、左上、左下及右下等四個向度。75位實驗參與者隨機分為四組，聆聽單一向度的音樂，並以語意反應及生理反應探測聆聽音樂時的情緒反應，再經由單因子變異數及CART分析探究各向度所具有的情緒特性。 結果發現右上向度具有「幽默」、「快樂」、「EMG上升」、「熱切」及「激動」等五種情緒特性；右下向度具有「幽默」、「快樂」、「EMG些微上升」、「低度熱切」及「Heart rate下降」等五種情緒特性；左上向度具有「嚴肅」、「激動或是平靜」、「低度沮喪」、「悲傷」及「溫度下降」等五種情緒特性；左下向度具有「嚴肅」、「激動」、「悲傷」、「沮喪」等四種情緒特性。 未來應用此技術，選取具備適當情緒特性的音樂，藉由音樂引發人們的情緒共鳴的特性，可應用於醫療、教育、娛樂及傳播媒體等方面。

The purpose of this study was to investigate the correlation among the signal patterns of four types of music including classical music, jazz, rock music, and pop in a total of 1,002 pieces of music. Then, investigate the relationship between signal patterns and emotion.The signal patterns of each piece of music were analyzed by MDS and formed a two-dimensional space scatter plots, which was divided into four quadrants (I: upper right; II: upper left; III: lower left; and IV: lower right) with origin coordinates (0, 0). Music with the greatest differences among the four quadrants were used in the experiments. Participants of the current study were randomly assigned into four groups. Each group listened to the music from one of the four quadrants and was tested for their emotional response by analyzing the data obtained from their semantic responses as well as physiological responses. One-way ANOVA and CART was used to analyze the emotional characteristics in each quadrant. Results indicated that the upper right quadrant(quadrant I) had five emotional characteristics such as ‘humorous’, ‘happy’, ‘increasing EMG’,’longing’and ‘agitated’; the lower right quadrant(quadrant IV) had five emotional characteristics such as ‘humorous’, ‘happy’, ‘slight increase in EMG’,’low level of longing’ and ‘decrease in heart rate’; the upper left quadrant(quadrant II) had five emotional characteristics such as ‘serious’, ‘agitated or calm’, ’ low level of depressed’, ’sad’ and ’ decrease in temperature’; the lower left quadrant(quadrant III) had four emotional characteristics such as ‘serious’, ‘agitated’ , ’sad’ , and’ depressed’. The future application of this method of choosing music with appropriate emotional characteristics to elicit corresponding emotions from individuals will bring benefits to the medical, educational, entertaining and media fields.