add figures that illustrate model layout

diff --git a/.gitignore b/.gitignore
index 8df797c..16f96cf 100644 (file)
--- a/.gitignore
+++ b/.gitignore
@@ -18,3 +18,4 @@
 *.tdo
 *.toc
 *.xdy
+*.png

diff --git a/Makefile b/Makefile
index b5714bc..62b3d23 100644 (file)
--- a/Makefile
+++ b/Makefile
@@ -7,29 +7,32 @@ MAKEGLOSSARIES?=makeglossaries
 MAKEGLOSSARIESFLAGS?=
 LATEXFLAGS:=-file-line-error -halt-on-error -no-shell-escape
 
+FIGURES:=$(addsuffix .png,$(addprefix img/,$(notdir $(basename $(wildcard fig/*.dot)))))
+LISTINGS:=$(wildcard listings/*)
+TEXS:=$(wildcard *.bib)
+BIBS:=$(wildcard *.tex)
+
 .PHONY: all clean
-.SECONDARY: $(addsuffix .fmt,$(DOCS))
+.SECONDARY: $(addsuffix .fmt,$(DOCS)) $(FIGURES)
 
 all: $(addsuffix .pdf,$(DOCS))
 
 %.fmt: %.pre
        $(LATEX) $(LATEXFLAGS) -ini -jobname="$(basename $@)" "&$(LATEX) $<\dump"
 
-%.pdf: %.tex %.fmt $(wildcard *.bib) $(wildcard *.tex)
+%.pdf: %.mlog
+       if $(GREP) -iFq 'Rerun' $<; then $(LATEX) $(LATEXFLAGS) $(basename $<); fi
+
+%.mlog: %.tex %.fmt $(BIBS) $(TEXS) $(FIGURES) $(LISTINGS)
        $(LATEX) $(LATEXFLAGS) $<
        if $(GREP) -q '^\\bibdata{' $(basename $<).aux; then $(BIBTEX) $(BIBTEXFLAGS) $(basename $<); fi
        if $(GREP) -q '\@istfilename' $(basename $<).aux; then $(MAKEGLOSSARIES) $(MAKEGLOSSARIESFLAGSFLAGS) $(basename $<); fi
-       $(LATEX) $(LATEXFLAGS) $< | tee $(basename $@).mlog 
-       $(GREP) -iFq 'Rerun' $(basename $@).mlog && $(LATEX) $(LATEXFLAGS) $< | tee $(basename $@).mlog || true
-       $(RM) $(basename $@).mlog
-
-clean: $(addprefix clean-,$(DOCS))
-
-clobber: $(addprefix clobber-,$(DOCS))
+       $(LATEX) $(LATEXFLAGS) $< | tee $@
 
-clean-%:
-       $(RM) $(addprefix $(@:clean-%=%).,acn acr alg aux bbl blg fmt glg glo gls\
-               ist lof log lol lot nav out run.xml snm tdo toc vrb xdy)
+img/%.png: fig/%.dot
+       dot -Tpng $< > $@
 
-clobber-%:
-       $(RM) $(@:clobber-%=%).pdf
+clean:
+       $(RM) $(foreach DOC,$(DOCS),$(addprefix $(DOC).,\
+               acn acr alg aux bbl blg fmt glg glo gls ist lof log lol lot nav out\
+               pdf run.xml snm tdo toc vrb xdy)) $(FIGURES)

diff --git a/appendices.tex b/appendices.tex
index 3faffc3..c5aadd9 100644 (file)
--- a/appendices.tex
+++ b/appendices.tex
@@ -3,7 +3,7 @@
        \centering
        \begin{tabular}{cll}
                \toprule
-               Num. & Song & Duration\\
+               Num. & Song & Duration (mm:ss.ss)\\
                \midrule
                \multicolumn{3}{l}{\bf Cannibal Corpse {-} A Skeletal Domain}\\
                00 & High Velocity Impact Spatter & 04:06.91\\

diff --git a/fig/bcann.dot b/fig/bcann.dot
new file mode 100644 (file)
index 0000000..608b740
--- /dev/null
+++ b/fig/bcann.dot
@@ -0,0 +1,31 @@
+digraph {
+       rankdir=LR;
+       graph [dpi=400,ordering=out,splines=false];
+       subgraph cluster_in {
+               label="Input"
+               i1 [label=<i<SUB>1</SUB>>];
+               i2 [label=<i<SUB>2</SUB>>];
+               id [label=<&hellip;>];
+               i13 [label=<i<SUB>13</SUB>>];
+       }
+
+       subgraph cluster_hidden {
+               label="Hidden"
+               h1 [label=<h<SUB>1</SUB>>];
+               h2 [label=<h<SUB>2</SUB>>];
+               hd [label=<&hellip;>];
+               hn [label=<h<SUB>n</SUB>>];
+       }
+
+       subgraph cluster_output {
+               label="Output"
+               o;
+       }
+
+       i1 -> h1; i1 -> h2; i1 -> hd; i1 -> hn;
+       i2 -> h1; i2 -> h2; i2 -> hd; i2 -> hn;
+       id -> h1; id -> h2; id -> hd; id -> hn;
+       i13 -> h1; i13 -> h2; i13 -> hd; i13 -> hn;
+
+       h1 -> o; h2 -> o; hd -> o; hn -> o;
+}

diff --git a/fig/mcann.dot b/fig/mcann.dot
new file mode 100644 (file)
index 0000000..495e141
--- /dev/null
+++ b/fig/mcann.dot
@@ -0,0 +1,37 @@
+digraph {
+       rankdir=LR;
+       graph [dpi=400,ordering=out,splines=false];
+       subgraph cluster_in {
+               label="Input"
+               i1 [label=<i<SUB>1</SUB>>];
+               i2 [label=<i<SUB>2</SUB>>];
+               id [label=<&hellip;>];
+               i13 [label=<i<SUB>13</SUB>>];
+       }
+
+       subgraph cluster_hidden {
+               label="Hidden"
+               h1 [label=<h<SUB>1</SUB>>];
+               h2 [label=<h<SUB>2</SUB>>];
+               hd [label=<&hellip;>];
+               hn [label=<h<SUB>n</SUB>>];
+       }
+
+       subgraph cluster_output {
+               label="Output"
+               o1 [label=<o<SUB>1</SUB>>];
+               o2 [label=<o<SUB>2</SUB>>];
+               od [label=<&hellip;>];
+               on [label=<o<SUB>n</SUB>>];
+       }
+
+       i1 -> h1; i1 -> h2; i1 -> hd; i1 -> hn;
+       i2 -> h1; i2 -> h2; i2 -> hd; i2 -> hn;
+       id -> h1; id -> h2; id -> hd; id -> hn;
+       i13 -> h1; i13 -> h2; i13 -> hd; i13 -> hn;
+
+       h1 -> o1; h1 -> o2; h1 -> od; h1 -> on;
+       h2 -> o1; h2 -> o2; h2 -> od; h2 -> on;
+       hd -> o1; hd -> o2; hd -> od; hd -> on;
+       hn -> o1; hn -> o2; hn -> od; hn -> on;
+}

diff --git a/methods.tex b/methods.tex
index a15c421..49f8426 100644 (file)
--- a/methods.tex
+++ b/methods.tex
@@ -50,6 +50,25 @@ and performs in several Muscovite bands. This band also stands out because it
 uses piano's and synthesizers. The droning synthesizers often operate in the
 same frequency as the vocals.
 
+The training and test data is divided as follows:
+\begin{table}[H]
+       \centering
+       \begin{tabular}{lcc}
+               \toprule
+               Singing & Instrumental\\
+               \midrule
+               0.59 & 0.41\\
+               \bottomrule
+       \end{tabular}
+       \quad
+       \begin{tabular}{lcccc}
+               \toprule
+               Instrumental & CC & DG & WDISS\\
+               \midrule
+               \bottomrule
+       \end{tabular}
+\end{table}
+
 \section{\gls{MFCC} Features}
 The waveforms in itself are not very suitable to be used as features due to the
 high dimensionality and correlation. Therefore we use the often used
@@ -84,9 +103,26 @@ steps.
 \section{\gls{ANN} Classifier}
 \todo{Spectrals might be enough, no decorrelation}
 
-\section{Model training}
-
 \section{Experiments}
+\subsection{\emph{Singing} voice detection}
+The first type of experiment conducted is \emph{Singing} voice detection. This
+is the act of segmenting an audio signal into segments that are labeled either
+as \emph{Singing} or as \emph{Instrumental}. The input of the classifier is a
+feature vector and the output is the probability that singing is happening in
+the sample.
+
+\begin{figure}[H]
+       \centering
+       \includegraphics[width=.5\textwidth]{bcann}
+       \caption{Binary classifier network architecture}\label{fig:bcann}
+\end{figure}
+
+\subsection{\emph{Singer} voice detection}
+The second type of experiment conducted is \emph{Singer} voice detection. This
+is the act of segmenting an audio signal into segments that are labeled either
+with the name of the singer or as \emph{Instrumental}. The input of the
+classifier is a feature vector and the outputs are probabilities for each of
+the singers and a probability for the instrumental label.
 
 \section{Results}