Emotion, Content, and Context in Sound and Music - Game Sound Technology and Player Interaction: Concepts and Developments - page 257

Figure 9. Wii Acceleration Curves for 3 States of Locomotion

against the emotional states extracted from the
user-scenario study and each song's E -state was
ranked against each scenario's E -state to provide
a grade for each song, using a simple Euclidean
distance measurement of the form

At this stage, it is recognised that the system
is currently more limited than the idealised sce-
nario presented earlier in Figure 8. A number of
factors have been simulated and a number of as-
sumptions have been made. However, using a
Fuzzy Rule Based System (FRBS) we have been
able to implement a limited version of the system
outlined in that dynamically outputs an E-state
based on live sensor data from a Wii controller
and simulated environmental parameters. An
outline of the Takagi-Sugeno-Kang (TSK) type

( ) 2

G p q ( , ) = p − q . (1)

Table 8 shows the resultant ranking of songs
(by their ID), for each of these scenarios.

Table 6. Range of Scenarios in Subject E-state Evaluation

ID Scenario Description

1 Walking, temperature is hot, lighting is dark/grey and weather is light rain.

2 Stationary, temperature is cold, lighting is dark and weather is raining.

3 Stationary, temperature is warm, lighting is brightening and weather is dry.

4 Running, temperature is hot, lighting is daylight/getting brighter and dry.

5 Walking, temperature is getting hot, lighting is dark and weather is drizzling.

6 Stationary, temperature is hot, lighting is grey and weather is dry.

7 Walking/Jogging, temperature is mild, daylight and it's dry.