Automatic Generation of Music for Inducing Physiological Response

Automatic Generation of Music for Inducing Physiological Response Kristine Monteith (kristine.perry@gmail.com) Department of Computer Science Bruce Brown(bruce brown@byu.edu) Department of Psychology Dan Ventura(ventura@cs.byu.edu) and Tony Martinez (martinez@cs.byu.edu) Department of Computer Science Brigham Young University Provo, UT 84602 USA Abstract Music is known to have a profound impact on human cogni- tive and emotional response, which in turn are strongly cor- related with physiological mechanisms. This paper presents a system that is designed to create original musical compositions that elicit particular physiological responses. The experiments described below demonstrate that the music generated by this system is as effective as human-composed music in effecting changes in skin resistance, skin temperature, breathing rate, and heart rate. The system is particularly adept at composing pieces that elicit target responses in individuals who demon- strated predictable responses to training selections. Keywords: music; emotion; perception; cognition; physiolog- ical response; targeted response Introduction Music can have a profound impact on human physiology. It affects how we think, how we feel, and how we relate to oth- ers. It captivates and holds our attention, stimulating many areas of the brain. From movie scenes to dance floors, the added sensory input of music makes activities and situations more enjoyable and compelling. One study found that plea- surable music activated the same areas of the brain activated by other euphoric stimuli such as food, sex, or drugs. They highlight the significance of the fact that music would have a similar effect on the brain as “biologically relevant, survival- related stimuli” (Blood & Zatorre, 2001). Music’s impact on human physiology may help explain its long-recognized ability to sway human emotion. It provides not only a medium for expressing a particular emotion, but also the accompanying physiological change to add signifi- cance and depth to that emotion. According to the Schachter- Singer theory, emotion is a function of both physiological arousal and cognitive interpretation of that response. The de- gree of arousal is associated with the degree of emotional re- sponse, but it is up to the individual to label that response according to past experience (Schachter & Singer, 1962). Music can also have significant power to calm the body and mind. While relaxation responses such as lowered breath- ing and heart rate may not be as closely tied with emotional perception and cognition, their elicitation can often have sig- nificant therapeutic benefits. Numerous studies have demon- strated the ability of music to induce a relaxation response (e.g White, 1999; Lepage et al., 2001; Khalfa et al., 2002). Both speed and accuracy of task performance can be en- hanced with relaxing music (Allen & Blascovich, 1994). While there is little question about whether or not music has an effect on humans, predicting the precise effect is chal- lenging. A few effects, however, do seem to be relatively consistent. For example, one study found that more com- plex rhythms tended to increase the rate of autonomic func- tions such as breathing and cardiovascular activity. Silence tended to have the opposite effect–lowering breathing rates and heart rates (Bernardi et al., 2006). White (1999) found that heart rate, respiratory rate, and myocardial oxygen de- mands were lower among patients recovering from myocar- dial infarctions; Khalfa et al. (2002) found that arousal re- sponses were more likely with pieces that the subjects found to communicate happiness or fear, while pieces described as sad or peaceful tended to decrease arousal. However, even these results only hold true for a majority of individuals. Finding a piece of music that would reliably effect a desired physiological response in a given individual remains a con- siderable challenge. Computer-generated music (Chuan & Chew, 2007; Cope, 2006) may provide some advantages in addressing this chal- lenge. Computers are well-suited to sifting through a large number of both large-scale and fine-grained musical features and to keeping track of which features will most likely have a particular effect. Indeed, some work has been done in gener- ating music to target a listener emotion or mood (Delgado et al., 2009; Rutherford & Wiggins, 2003; Oliveira & Cardoso, 2007). In addition, a human composer might be more biased towards features that would effect his or her own physiol- ogy when producing compositions. While a reliance on one’s own physiological experiences may be inspiring and helpful in the creative process, when it comes to eliciting physiolog- ical responses from others, it may also sometimes result in pieces that are less generalizable. Additionally, once they have “learned” how to do so, computers can generate large quantities of music at virtually no cost in terms of time or ef- fort. A computer would have a much easier time generating a number of different potential compositions to effect a desired result in a given individual until it happened upon the right one. Therefore, the ability of a computer to compose music that elicits a target response could have significant benefits.