Using Emotion Map System to Implement the Generative Chinese Style Music with Wu Xing Theory

Using Emotion Map System to Implement the Generative Chinese Style Music with Wu Xing Theory

Chih-Fang Huang (Department of Information Communications, Kainan University, Taiwan) and En-Ju Lin (Department of Musicology, Heidelberg University, Germany)
DOI: 10.4018/978-1-4666-4490-8.ch018
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Wu Xing is an ancient mysterious Chinese philosophy applied to many fields. The Music Emotion Classification (MEC) refers to the music cognition of mind with the categorized emotion result mapping to music parameters. Many researchers focused the topic on the MEC with theory and experiment development in the past decades. This chapter mainly discusses the possibility to synthesize the meta-level algorithmic music based on the analysis result from the previous research, with the proposed Emotion Map System (EMS) mapped into the innovated Wu Xing Emotion Map System (WXEMS), which indicates the emotion situation based on the X-Y coordinate movement in the WXEMS plane. The MEC result shown in the EMS/WXEMS trajectory controls the algorithmic music variation with the proposed mapping rules. In addition, the generative music varies smoothly according to the correspondent WXEMS data changed with any emotion transition, which can apply the technology into the generative background music in Chinese style using the proposed Wu Xing Automated Music System (WXAMS).
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There are lots of research literatures show the relationship between music and emotion. Chinese Wu Xing (Fung, 1983; Wolfram, 1965) which means five elements, including metal, wood, water, fire, and earth, respectively, provides an abstract and mysterious philosophy applied for various fields including Chinese medicine, Cosmology or so-called Feng Shui, military strategy, and music, to pursuit the harmony in human and nature. In this chapter the music emotion classification (MEC) will be discussed, and correlated to Wu Xing theory, in order to generate background music in Chinese style automatically.

Some of the music emotion researches retrieved the data from the speech, facial expression, and physiological signal (Healey, 2000; Picard, Vyzas & Healey, 2001; Haag, Goronzy, Schaich & Williams, 2004; Nasoz, Alvarez, Lisetti & Finkelstein, 2003), which are not sufficiently acceptable for the realistic application. The research by Johannes Wagner, Jonghwa Kim, Elisabeth André (Chen, 1996) shows a successful emotion recognition system including data analysis and classification for collecting physiological signals indifferent affective states for music and emotion with biosensors. Therefore we adopt and categorize the four emotions including “joy”, “anger”, “sadness”, and “pleasure” to the well-know 2-D emotion model into the 4-quadrature plane, according to Johannes Wagner’s expression. The horizontal axis (X-axis) with position and negative directions represents the “positive emotion” and “negative emotion” respectively, while the vertical axis (Y-axis) in positive and negative directions represents the “high arousal / energetic” and “low arousal / calm” emotions respectively. Figure 1 shows our proposed 2-D Emotional Model for the generative music with the “Emotion Trajectory” controlled by user, with proper emotion-music features mapping into our proposed “emotion map system” (EMS) to generate music automatically (Huang, 2011).

Figure 1.

The 2-D Emotional Map System (EMS) in a 4-quadrature plane


Wu Xing Music Theory

The proposed Wu Xing generative music is based on the fundamental Chinese Wu Xing philosophy (Fung, 1983; Wolfram, 1965; Rossi, Caretto & Scheid, 2007), and the properties metal, wood, water, fire, and earth construct this system as a universe. Chinese pentatonic scale will be discussed to map the Wu Xing emotion data correlated to the MEC system.

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