# Timbre Preferences in the Context of Mixing Music
## 6 Results
### Participant Correlations and Clustering  
The correlations between the participants in their mixing behavior, as illustrated in Figure 4, shows a small group of highly correlated participants (4, 9, 15, 23, 28, and to a lower degree 11, 13, 19, 20, 25, 27) and a large group of other participants behaving independently to those two groups and each other. The correlations go as high as 0.74 for some of the participants.  
A hierarchical clustering of the same data (divided by participants), done with the linkage and dendrogram functions of Matlab 2014, shows a similar result (Figure 5), but identifies two groups of participants clustering with shorter data point distances (6, 27, 14 and 4, 15, 9, 23, 13, 11, 21, 28) and the larger group of other participants further apart.  
A \(k\)-means cluster analysis of the slider data was conducted to find specific mixing clusters that might arise. The result shows the silhouette value for a clustering into two groups being highest. Plotting all slider settings in a 4-D space and splitting into the two clusters in Figure 6 suggest the OER value to be the primary deciding factor between the two groups.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Effect** & **Estimate** & **Est.Error** & **l–95\% CI** & **u–95\% CI** \\ \hline MixE & \(-\)0.3 & 0.22 & \(-\)0.74 & 0.13 \\ MixR & \(-\)0.35 & 0.22 & \(-\)0.77 & 0.08 \\ MixP & \(-\)0.59 & 0.22 & \(-\)1.01 & \(-\)0.16 \\ MyMix & \(-\)0.95 & 0.18 & \(-\)1.31 & \(-\)0.58 \\ MixS:GMSI & \(-\)0.53 & 0.3 & \(-\)1.12 & 0.07 \\ MixE:GMSI & \(-\)0.32 & 0.29 & \(-\)0.88 & 0.25 \\ MixR:GMSI & 0.16 & 0.32 & \(-\)0.47 & 0.78 \\ MixP:GMSI & \(-\)0.05 & 0.30 & \(-\)0.64 & 0.54 \\ \hline \end{tabular}
\end{table}
Table 2: The output of the Bayesian model with MixS as the reference level. The Estimate is the mean of each effect’s posterior distribution, l–95% and u–95% are the lower and upper bounds of the effects’ 95% credibility interval (the data tell us that the effect’s true size has a 95% probability of falling in this interval), respectively. If the 95% CI (Confidence Interval) does not cross zero, the effect can be considered “significant”. MixY:GMSI effects are the interaction effects between Goldsmith Music Sophistication Index (GMSI) and the specified mix ratings. MixS = Sawtooth Mix, MixP = Personal Mix, MixE = Expert Mix, MixR = Random Mix.Population-Level Effects.  
\begin{table}
\begin{tabular}{c c} \hline
**Mix** & **Identified as Own** \\ \hline Personal: & 28\% \\ Random: & 17\% \\ Sawtooth: & 25\% \\ Expert: & 30\% \\ \hline \end{tabular}
\end{table}
Table 3: Percentage of mixes being identified as the participants own.  
Figure 4: Schemaball illustration of Pearson correlations between participants. The numbers around the circle represent the participants, the color of the connecting lines (green to white to blue) represents the coefficient, and the color of the dots next to the number represents the average coefficient of the participant.  
Figure 5: Dendogram of hierarchical clustering of participants; the \(x\)-axis represents the relative distance of individual participants, with the color cut-off being 60% of the biggest distance.  
In the post-task questions, all of the participants, save for one, indicated thinking to have been able to improve on the mixes at least to some degree. Most of them used a mixture of \"SOLO\" and \"FullMix\" modes. They usually utilized either no particular mixing strategy or a variety of different ones. Participants either tried to eliminate unpleasant parts of the sound to adjust the level of sounds by timbral means or to overall improve \"clarity\", although some answers are difficult to interpret (\"[...] the strategy was P H A T, with a capital P!\").