Syncing to home.

main.tex

@@ -1120,7 +1120,7 @@ in principle, work together towards an intensity-invariant song representation.
     \centering
     \includegraphics[width=\textwidth]{figures/fig_invariance_full_Omocestus_rufipes.pdf}
     \caption{\textbf{Step-wise emergence of intensity-invariant song
-                     representation along the full model pathway.}
+                     representations along the model pathway.}
                      Input $\raw(t)$ consists of song component $\soc(t)$
                      scaled by $\sca$ with added noise component $\noc(t)$ and
                      is processed up to the feature set $f_i(t)$. Different
@@ -1201,9 +1201,8 @@ guaranteed simply by disabling logarithmic compression.
 \begin{figure}[!ht]
     \centering
     \includegraphics[width=\textwidth]{figures/fig_invariance_short_Omocestus_rufipes.pdf}
-    \caption{\textbf{Step-wise emergence of intensity invariant song
-                     representation along the model pathway without logarithmic
-                     compression.}
+    \caption{\textbf{Effects of disabling logarithmic compression on intensity
+                     invariance along the model pathway.}
                      Input $\raw(t)$ consists of song component $\soc(t)$
                      scaled by $\sca$ with added noise component $\noc(t)$ and
                      is processed up to the feature set $f_i(t)$, skipping
@@ -1235,13 +1234,41 @@ guaranteed simply by disabling logarithmic compression.
 \end{figure}
 \FloatBarrier
 
-\subsubsection{Field data}
+\subsubsection{Intensity invariance in a naturalistic setting}
+
+So far, the analyses on intensity invariance were based on synthetically
+generated input signals, since these allow for a systematic manipulation of
+the mixture of song component $\soc(t)$ and noise component $\noc(t)$ over
+an arbitrary range of scales $\sca$.
 
 \begin{figure}[!ht]
     \centering
     \includegraphics[width=\textwidth]{figures/fig_invariance_field.pdf}
-    \caption{\textbf{Step-wise emergence of intensity invariant song
-                     representation along the model pathway.}
+    \caption{\textbf{Intensity invariance along the model pathway in a 
+                     naturalistic setting.}
+                     Input $\raw(t)$ consists of a song of \textit{P.
+                     parallelus} recorded in the field at eight different
+                     distances $d$ and is processed up to the feature set
+                     $f_i(t)$. Different color shades indicate different types
+                     of Gabor kernels with specific lobe number $\kn$ and
+                     either $+$ or $-$ sign, sorted (dark to light) first by
+                     increasing $\kn$ and then by
+                     sign~($1\,\leq\,\kn\,\leq\,4$; first $+$, then $-$ for
+                     each $\kn$; five kernel widths $\kw$ of 1, 2, 4, 8, and
+                     $16\,$ms per type; 8 types, 40 kernels in total).
+                     \textbf{a}:~$\filt(t)$, $\env(t)$, $\db(t)$, $\adapt(t)$,
+                     $c_i(t)$, and $f_i(t)$ at each $d$. A noise segment from
+                     the same recording is shown for reference.
+                     \textbf{b}:~Intensity metrics over $d$. For $c_i(t)$
+                     and $f_i(t)$, the median over kernels is shown.
+                     \textbf{c}:~Average value $\mu_{f_i}$ of each feature
+                     $f_i(t)$ over $d$.
+                     \textbf{d}:~Ratios of intensity metrics to the respective
+                     value obtained from the noise reference. For $c_i(t)$ and
+                     $f_i(t)$, the median over kernel-specific ratios is shown.
+                     \textbf{e}:~Ratios of standard deviation $\sigma_{c_i}$ of
+                     each $c_i(t)$.
+                     \textbf{f}:~Ratios of $\mu_{f_i}$.
                      }
     \label{fig:pipeline_field}
 \end{figure}