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Ostateczna wersja pracy magisterskiej

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CezaryPukownik 2020-07-11 14:50:46 +02:00
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[]\OT4/cmr/m/n/12 Gdy zde-fi-nio-wa-ne mo-de-le zo-sta-n¡ wy-tre-no-wa-ne mo-»e-my wy-ko-rzy-sta¢ skrypt
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@ -13,6 +13,7 @@
\usepackage{subfig}
% \usepackage[T1]{fontenc}
\newcommand{\textoperatorname}[1]{
\operatorname{\textnormal{#1}}
}
@ -97,11 +98,11 @@
\vspace{3cm}
\hspace{7.5cm}{Praca magisterska}\\[-12pt]
\hspace{6cm}{Praca magisterska}\\[-12pt]
\hspace{7.5cm}{napisana pod kierunkiem}\\[-12pt]
\hspace{6cm}{napisana pod kierunkiem}\\[-12pt]
\hspace{7.5cm}{dra hab. Tomasza Góreckiego}
\hspace{6cm}{prof. UAM dra hab. Tomasza Góreckiego}
\vspace{2.2cm}
@ -116,7 +117,7 @@
\thispagestyle{empty}
\begin{flushright}
Poznań, dnia 27.06.2020
Poznań, dnia 30 czerwca 2020
\end{flushright}
\vglue 2.4 cm
@ -127,11 +128,12 @@ Poznań, dnia 27.06.2020
\vglue 1.2 cm
Ja, niżej podpisany Cezary Pukownik, student Wydziału Matematyki i Informatyki Uniwersytetu im. Adama Mickiewicza w Poznaniu oświadczam, że przedkładaną pracę dyplomową pt: "Generowanie muzyki przy pomocy głębokiego uczenia", napisałem samodzielnie. Oznacza to, że przy pisaniu pracy, poza niezbędnymi konsultacjami, nie korzystałem z pomocy innych osób, a w szczególności nie zlecałem opracowania rozprawy lub jej części innym osobom, ani nie odpisywałem tej rozprawy lub jej części od innych osób.
Ja, niżej podpisany student Uniwersytetu im. Adama Mickiewicza w Poznaniu oświadczam, że przedkładaną pracę dyplomową napisałem samodzielnie. Oznacza to, że przy pisaniu pracy, poza niezbędnymi konsultacjami, nie korzystałem z pomocy innych osób, a w szczególności nie zlecałem opracowania rozprawy lub jej części innym osobom ani
nie odpisywałem tej rozprawy lub jej części od innych osób.
Oświadczam również, że egzemplarz pracy dyplomowej w wersji drukowanej jest całkowicie zgodny z egzemplarzem pracy dyplomowej w wersji elektronicznej.
Jednocześnie przyjmuję do wiadomości, że przypisanie sobie w pracy dyplomowej autorstwa istotnego fragmentu lub innych elementów cudzego utworu lub ustalenia naukowego stanowi podstawę stwierdzenia nieważności postępowania administracyjnego w sprawie nadania tytułu zawodowego.
Jednocześnie przyjmuję do wiadomości, że przypisanie sobie, w pracy dyplomowej, autorstwa istotnego fragmentu lub innych elementów cudzego utworu lub ustalenia naukowego stanowi podstawę stwierdzenia nieważności postępowania w sprawie nadania tytułu zawodowego.
Ja, niżej podpisany student Uniwersytetu im. Adama Mickiewicza w Poznaniu oświadczam, że egzemplarz pracy dyplomowej w wersji drukowanej jest całkowicie zgodny z egzemplarzem pracy dyplomowej w wersji elektronicznej.
\bigskip
@ -148,7 +150,6 @@ Jednocześnie przyjmuję do wiadomości, że przypisanie sobie, w pracy dyplomow
\vglue 2 cm
\hglue 6cm ............................................................
% Koniec oświadczenia
% #######################################################
@ -605,7 +606,7 @@ The rest of this chapter discusses an example of using the proposed model to gen
\label{fig:note_len}
\end{figure}
\footnotetext{https://www.infomusic.pl/poradnik/46934,poradnik-teoria-muzyki-rytm
\footnotetext{infomusic.pl/poradnik/46934,poradnik-teoria-muzyki-rytm
\newline
5 kwietnia 2020 12:46}
@ -648,7 +649,7 @@ The rest of this chapter discusses an example of using the proposed model to gen
\label{fig:pieciolinia}
\end{figure}
\footnotetext{https://amplitudaschool.weebly.com/lekcja-11.html 5 kwietnia 2020 13:24}
\footnotetext{amplitudaschool.weebly.com/lekcja-11 5 kwietnia 2020 13:24}
\subsubsection{Interwał}
O interwałach mówimy kiedy porównujemy ze sobą dwie nuty. Interwał jest to odległość między nutami liczona w półnutach. Półnuta jest to najmniejsza odległość między nutami we współczesnej notacji muzycznej. Oktawa jest podzielona na 12 równych części. Pomiędzy dźwiękami C i D jest odległość
@ -748,7 +749,8 @@ note_on channel=0 note=60 velocity=0 time=0
% https://www.midi.org/specifications-old/item/gm-level-1-sound-set
\footnotetext{https://alchetron.com/ 16 czerwca 2020 8:23}
\footnotetext{alchetron.com/General-MIDI\#general-midi-d016a071-b750-46c2-8828-926e6d2aa12
-resize-750.png 16 czerwca 2020 8:23}
% https://alchetron.com/General-MIDI#general-midi-d016a071-b750-46c2-8828-926e6d2aa12-resize-750.png
\subsubsection{Ścieżka}
@ -1137,7 +1139,8 @@ Aby otrzymać model gotowy do procesu uczenia należy połączyć ze sobą enkod
\label{fig:training-model}
\end{figure}
\footnotetext{machinelearningmastery.com 16 czerwca 2020 06:24}
\footnotetext{machinelearningmastery.com/define-encoder-decoder-sequence-sequence-model-neural-
machine-translation-keras 16 czerwca 2020 6:24}
\begin{python}
self.train_model =
@ -1187,11 +1190,12 @@ self.decoder_model = Model(
\begin{figure}[!htb]
\centering
\includegraphics[width=\linewidth]{images/inference-decoder-graph.png}
\caption[]{Model seq2seq w trybie uczenia\footnotemark}
\caption[]{Model seq2seq w trybie wnioskowania\footnotemark}
\label{fig:inference-decoder}
\end{figure}
\footnotetext{machinelearningmastery.com 16 czerwca 2020 06:24}
\footnotetext{machinelearningmastery.com/define-encoder-decoder-sequence-sequence-model-neural-
machine-translation-keras 16 czerwca 2020 6:24}
Dzięki takiej definicji jesteśmy w stanie w pętli przewidywać następne elementy do momentu osiągnięcia warunku stopu. Implementacja tego procesu wygląda tak:
@ -1629,25 +1633,29 @@ Na rysunku~\ref{fig:score100} i rysunku~\ref{fig:score150} przedstawiono odpowie
\bibitem{survay} Briot, J.P., Hadjeres, G., Pachet, F.D. (2019): {\em Deep Learning Techniques for Music Generation - A Survey. arXiv:1709.01620v3}
\bibitem{seq2seq-keras} Brownlee, J. (2017): {\em How to Develop a Seq2Seq Model for Neural Machine Translation in Keras, machinelearningmastery.com}
\bibitem{seq2seq-keras} Brownlee, J. (2017): {\em How to Develop a Seq2Seq Model for Neural Machine Translation in Keras, machinelearningmastery.com/define-encoder-
decoder-sequence-sequence-model-neural-machine-translation-keras, 16 czerwca 2020 06:24}
\bibitem{onehot} DeepAI (2019): {\em One Hot Encoding, deepai.org}
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glossary-and-terms/one-hot-encoding, 12 czerwca 2020 18:52}
\bibitem{handson} Géron, A. (2019): {\em Hands-on machine learning with scikit-learn, keras and TensorFlow. O'Reilly.}
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\bibitem{keras} Keras Team, (2020): {\em Keras: the Python deep learning API, keras.io}
\bibitem{keras} Keras Team, (2020): {\em Keras API reference, keras.io/api, 17 sierpnia 2019 12:34 }
\bibitem{seq2seq} Kostadinov, S. (2019): {\em Understanding Encoder-Decoder Sequence to Sequence Model, towardsdatascience.com}
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sequence, 15 maja 2020 15:34}
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\bibitem{pretty_midi} Raffel, C. (2020): {\em pretty\textunderscore midi, pypi.org}
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\bibitem{tempos} Swinney, A. (2020): {\em What is a tempo marking?, classicalmusiccity.com}
\bibitem{tempos} Swinney, A. (2020): {\em What is a tempo marking?, classicalmusiccity.com/search/
article.php?vars=446/Basic-Tempo-Markings.html, 5 kwietnia 2020 19:37}
\bibitem{deep_learning_2} Zocca, V., Spacagna, G., Slater, D., Roelants, P. (2018): {\em Deep Learning. Uczenie głębokie z językiem Python. Helion.}