Emotion, Content, and Context in Sound and Music - Game Sound Technology and Player Interaction: Concepts and Developments - page 246

Figure 4. ASM of ABBA's “Head Over Heels” (28 second sample)

good starting point to stimulate the imagination
into how content analysis can provide highly useful
information for a variety of scenarios. A graphical
example of an ASM is presented in Figure 4 as
an exemplar, where dark colours represent high
similarity and bright colours show low similarity.
Whilst we do not limit the application of con-
tent analysis to computer games, we suggest a
few examples of appropriate situations where it
may be used. Simple examples relate to the link
between visuals and sound. In a game where the
scene is bright and full of strong, primary colours,
it would be pertinent to include sound that reflects
this notion: bright and strong in timbre. On the
other hand, a dark, oppressive scene would require
slower, darker music with a thinner and sharper
timbre, inducing a different set of emotions. In
today's dynamic computer games, where the user
has an apparently boundless freedom to explore
a virtual environment, the dynamic updating of
sound content to match the visuals requires some

form of content analysis. Even a simple param-
eter that defined the “colour” of the scene or
presence of tagged objects nearby would suffice
on a basic level. Another suggestion would be to
manipulate the gameplay by the choice of music
and sound prescribed by the user. For example,
the same game scenarios and task may be under-
taken at different speeds, levels of difficulty, and
in different environments, based upon the choice
of music the user makes. Consider the scenario
where a user may decide to play dance music
whilst interacting with a game, thereby instigating
a bright, quantised environment with predictable,
rhythmic, structured gameplay content. Whereas
if they choose highly random, noisy, alternative
noise-core they would be presented with chaotic,
overwhelming game scenarios: in both cases, a
reflection of the structure and content of the mu-
sic that can be achieved only through detailed
signal and structural content analysis of the audio
data.