# Dynamic Range Compression and the Semantic Descriptor Aggressive
## 2 Qualitative Studies
### Similarity Matrix  
To help clarify the meaning of the descriptors, a second stage asked respondents to rate the appropriateness of the most popular descriptors in describing the sound quality of a given compression technique. The compression techniques were: linear processing, colouration general, colouration frequency related, distortion, modulation/altering rhythmic feel, general dynamic range control, attenuating transient and accentuating transient. The author selected these techniques based on prior research [24] which indicated these practices were commonly used by industry professionals when applying dynamic range compression. Respondents completed the task online and recorded their scores on a similarity matrix. This was conducted by creating an online spreadsheet that had compression activities on the X-axis and descriptors on the Y-axis. Respondents then allocated each descriptor a score between zero and four to rate its appropriateness (zero being totally inappropriate and four being totally appropriate). As a descriptor could relate to more than one compression technique, the respondents were instructed to rate the descriptor for as many techniques as they felt appropriate. The use of similarity matrices to look for associations between audio descriptors has been used in several previous studies [25; 26; 27; 28]. The similarity matrix was completed by twelve experts, all of which had participated in the previous stage. The results were averaged to take the mean score for each descriptor and clustering was conducted using the Euclidean distance and Ward methods. The statistical software R was used to generate the dendrogram shown in Figure 1. As shown in the dendrogram, there are several subsets, illustrated in brown, green, blue and grey. Inspection of the grey subset highlights descriptors which appear to fall into two main categories, one relating to dynamics and the other pertaining to colouration and distortion (linear and non-linear distortion). Looking at a lower branch in the dendrogram highlights that aggressive is grouped with, among other words, attitude, energy and smashed. All of these words are subjective and have not been defined in any of the previous literature. Moreover, one could argue these descriptors relate to the character of the compressor and are potentially multi-dimensional attributes. Referring back to the descriptors used in Table 1, this shows that contentions made previously regarding the meaning of these words are generally correct. As an example, the terms dirt and gritty are connected to distortion in the brown subset. Pumping is connected to ambience (which is understandable as compression-related amplitude modulation often manifests as quick changes in the amplitude of the ambience present in the program material). Finally, punch is connected to definition and also attack, which would support the notion that this descriptor is related to the manipulation of transient shapes. \begin{table}
\begin{tabular}{c c} \hline \hline
**Descriptor** & **Frequency of Occurrence** \\ \hline Aggressive & 6 \\ Gritty & 5 \\ Forward & 4 \\ Midrange & 4 \\ Presence & 4 \\ Full & 3 \\ Sparkly & 2 \\ Up Front & 2 \\ Pumping & 2 \\ Smooth & 2 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Descriptors used for 1176 vocal compression. To get a better understanding of the descriptor aggressive, the focus of this study, statistical analysis was conducted on the mean scores allocated by the respondents to the compression techniques in relation to the term aggressive. The results show that there was a statistically significant difference between groups (compression techniques), as determined by one-way ANOVA (F (7,88) = 3.854, \(p\) = 0.001). A Tukey post-hoc test revealed that the experts considered the descriptor aggressive was statistically significantly lower for the compression techniques \"general dynamic range control\" (\(p\) = 0.027), \"modulation\" (\(p\) = 0.002) and \"linear processing\" (\(p\) = 0.001) compared to the compression technique \"distortion\".