1 research outputs found
Towards general models of player affect
While the primary focus of affective computing has
been on constructing efficient and reliable models of affect,
the vast majority of such models are limited to a specific task
and domain. This paper, instead, investigates how computational
models of affect can be general across dissimilar tasks; in
particular, in modeling the experience of playing very different
video games. We use three dissimilar games whose players
annotated their arousal levels on video recordings of their own
playthroughs. We construct models mapping ranks of arousal to
skin conductance and gameplay logs via preference learning and
we use a form of cross-game validation to test the generality of the
obtained models on unseen games. Our initial results comparing
between absolute and relative measures of the arousal annotation
values indicate that we can obtain more general models of player
affect if we process the model output in an ordinal fashion.peer-reviewe