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2.0 - Literature draft

I've been reading about a lot of different things and it is time to focus. Right now there are multiple ways I can solve the music generator problem. One is through Recurrent Neural Networks (RNN's) there is Convolutional Neural Networks (CNN's) and there is a combined approach in which I use a CNN combined with a Generative Adversarial Network (GAN). This amounts to a state of the art approach. RNN's are easier to train and capable of generating good midi files (when listeners proof it) while maintaining structural cohesion in an Encoder Decoder model (EDM). This is a method gives the hidden node states of the Encoder model to the Decoder model to obtain a certain level of music generation that is high level enough to be interesting for my project. However, as it is proven that it is possible to use 2D data as well in RNN's the only reason to choose a CNN & GAN combination is because it has been done in only one paper I found before. While RNN's have been w...
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One is the essence that binds us all

Boulevard of broken dreams, nothing is at though it seems.  And I don't even love you at all, now I just let go and fall.  Take me to a better place, I go through this pain to face.  A loving direction and call, I take my first step, it's small.  I want to uproot my life and change, because I've ended up feeling strange.  A stranger in my own life, a stranger in my own life.  I take my time to contemplate, I stand in front my inner gate.  A portal into my heart and soul, I start to feel blessed and hear my call.  Send this vibration to space, uplift the whole human race.  In this field of forgiveness and grace, I feel at home in this place.  Through the challenges I had to face, I feel empowered  Trust in yourself and your strong heart steps forth  Mind body and soul, all in accord  Agree with your heartmind body and soul  You are a survivor, a king, a whole  Generous, gracious, not greedy at all  Let it al...
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4.1 - Redefining overall structure

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As seen in this updated mindmap below, there is a lot going on internally when making music, but there also is emotional influence of the listener, either intended or not, by the maker. This makes for a more wholesome structure of the research field and includes all the different parts that make music in itself an interesting thing to study.  When looking into the technical details of making an artificial music generator there is a part which analyses data, implements learned details (which melodic and song structure are made up of)  and the actual generator part which uses the aforementioned learned details and rules to generate music.  In a set up with GANs there is the possibility to generate more data with the encoder, while the decoder is fed this information to discriminate between. The encoder is therefore atuned to generate different types of subsets and learns better what the difference with the original data set is. The sequential aspect of music ma...
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