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For the second part of my thesis I talk about how I came to create the creative project aspect. I discuss how and why I designed the narrative that I did, and also analyzed the music I have created to illustrate how I implemented the various methods of musical storytelling that I detail in the first part of the paper. Lastly, I discuss my plans for publication and release of the creative project.
The third part of this thesis is a sample of the creative project. There is a version of the narrative that goes along with the creative project, as well as one of the eight pieces of original music on the creative project, entitled Journey.
Overall, I found that music does have meaning, it is just meaning that society ascribes to it based off of artistic intent and context, and as to whether music should mean anything, I believe that this is a question best left to be answered on an individual basis. Music can be whatever it wants to be.
This thesis evaluates how films from Western Europe portray the social, political and economic degradation that allows the American influence to rise leading up to the Cold War. Specifically, this thesis evaluates classic films from Weimar Germany, the Soviet Union, post-fascist Italy and post-Vichy France as historical and cultural artifacts that depict the harsh conditions of postwar life and how American influence revitalized daily European life. While the American influence (defined as the support of democracy, technological modernization and a capitalist economy) was supported by many struggling Europeans who looked to the United States as a standard to rebuild, critics from each country viewed American influence as a threat to the stability of national independence which they sought to maintain as recovery balanced postwar society.
The verses generated by the system are evaluated using rhyme, rhythm, syllable counts and stress patterns. These computational features of language are considered for generating haikus, limericks and iambic pentameter verses. The generated poems are evaluated using a Turing test on both experts and non-experts. The user study finds that only 38% computer generated poems were correctly identified by nonexperts while 65% of the computer generated poems were correctly identified by experts. Although the system does not pass the Turing test, the results from the Turing test suggest an improvement of over 17% when compared to previous methods which use Turing tests to evaluate poetry generators.