Add some rather unstructured content.

1 files changed, 26 insertions, 2 deletions

diff --git a/sampling_alg_lac2020/LAC-20.tex b/sampling_alg_lac2020/LAC-20.tex
index 8a56d1f..b4a4648 100644
--- a/sampling_alg_lac2020/LAC-20.tex
+++ b/sampling_alg_lac2020/LAC-20.tex
@@ -195,7 +195,7 @@
 \newcommand{\todobent}[1]{\textcolor{blue}{\textbf{TODO (Bent):} #1}}
 
 % ugly hack
-\renewcommand{\paragraph}[1]{\textbf{#1}. }
+\renewcommand{\paragraph}[1]{\textbf{#1} }
 
 % ====================================
 
@@ -429,8 +429,13 @@ Note that the worst-case complexity of evaluating the objective function is line
 
 \section{Emulation Capabilities}
 \todo{Talk about which other algorithms we are a general case of, i.e., which algorithms can we emulate using the right power values and parameter settings.}
+The main advantage of the described sampling algorithm is that it can emulate the most common sample choice algorithms. In the following we describe which algorithms can be emulated and how we have to set the parameters and power values for that.
 
-\section{Implementation}
+\paragraph{Round Robin.} bla
+
+\paragraph{Which other??} bla
+
+\section{Implementation} \label{sec:implementation}
 \todobent{Give a short introduction to DrumGizmo, including a link to the git repository.}
 \todo{Talk about the timeline, i.e., when were the releases and what is still unreleased?}
 
@@ -456,10 +461,29 @@ Note that by traversing the samples in order of their distance to $p$ (which is
 
 \section{Experiments}
 \todoandre{Talk about the setup.}
+We conducted experiments with the implementation of the new sampling algorithm in DrumGizmo.
+As a comparison we use the previous sample selection algorithm of DrumGizmo.
+To get experiments that show how the sample selection algorithm performs in practice, we use the drum kits of DrumGizmo. We do experiments on three different drum kits. See Figure \ref{fig:drumkit_data} and Table \ref{tab:drumkit_data} for some information about the samples of the drum kits and a visualization of the power level distribution of the different kits.
+
 \todoandre{Talk about what the experiments should show: two close samples are chosen similarly often; playing the same MIDI note plays a reasonably varied sample set; average distance of one sample}
+We want to test the following hypotheses with our experiments:
+\begin{enumerate}
+	\item Two samples with similar power values are chosen similarly often.
+	\item Playing the same MIDI note over and over again plays a reasonably varied set of samples.
+	\item Average distance of one sample \todo{what did I want to say with that?}
+\end{enumerate}
 \todoandre{Experiments are: playing fast sweeps (with multiple hits per velocity); playing a single note over and over again at the same velocity; sound examples that people can listen to online?}
+To test the above hypotheses, we conduct the following experiments:
+\begin{enumerate}
+	\item Playing fast sweeps over the whole velocity range.
+	\item Playing a single note at high velocity.
+\end{enumerate}
+
 \todoandre{Do beautiful tables and plots here}
+
 \todoandre{Also do an experiment regarding the adaptive search}
+To also experimentally test the performance of the new sampling algorithm, we want to see how many sample power values are evaluated per query. Especially, we expect that the smart search optimization described at the end of Section \label{sec:implementation} reduces the number of evaluations significantly.
+
 \todoandre{Summarize experiments}
 
 \section{Conclusion and Future Work}