Article Preview
Top1. Introduction
Music is not only a form of art but also a language that expresses human emotions, inner modes, and affective information (Juslin, 2001; Rodriguez, Ramos, & Wang, 2012; Wilson, and Keil, 2001; Juslin, & Sloboda, 2001). It is generally believed that music cannot be composed, performed, or comprehended without affective cognition and involvement. Music expresses affective emotions including joy, happiness, annoyance, sadness, pain, etc. Aesthetics and cognitive science recognize music as an effective form of affective expression. However, music experience is a subjective behavior in the process of music creation or appreciation. Individuals may have different understanding of the same piece of music and different extend of affective emotional effects. Therefore, how the affective emotions of music are formally evaluated is a challenging problem in fields of musicology, esthetics, psychologists, and cognitive science (Juslin, 2001; Hallam, & Thaut,2008). At present, machine learning algorithm is the research hotspot (Wang, 2016, 2015, 2015), and the machine learning algorithms are widely adapted to the recognize music emotions (Yang et al., 2008; Bang et al.,2013; Mokhsin et al.,2014; Jens, and Sand et al., 2015; Chin, and Lin et al, 2013).
In 1980s, Russell and Thayer proposed the Valence - Arousal model for music emotion description which is widely accepted and used by musicologists, estheticians and psychologists (Russell, 1980). A 2D emotion plane is introduced in the dimensions of valence and arousal (VA). In AV plane, the horizontal axis is defined as valence values representing a positive or negative emotion. The vertical coordinate is defined as arousal values of exciting or calming. Both VA values are ranged in (-1, 1). In this measurement scope, a valence value closer to 1 means a higher and positive emotions, and vice versa. Similarly, a higher arousal value indicates a stronger emotional intensity, and vice versa.
For example, as shown in Figure 1, a happy feeling is an emotion of positive valence and highly arousal, while sad is an emotion of negative valence and low arousal. Therefore, any form of music emotion can be mapped to the AV plane as a certain point. This allows music emotions to be formally recognized by a pair of VA values (Thayer, 1989). This dimensional conceptualization of music emotions provides a simple, reliable, and understandable model for practical affective experiments and manipulations.
Figure 1. The valance-arousal plane of music emotions