Automatic Embedding of Stories Into Collections of Independent Media
Automatic Embedding of Stories Into Collections of Independent Media
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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We look at how machine learning techniques that derive properties of items in a collection of independent media can be used to automatically embed stories into such collections. To do so, we use models that extract the tempo of songs to make a music playlist follow a narrative arc. Our work specifies an open-source tool that uses pre-trained neural network models to extract the global tempo of a set of raw audio files and applies these measures to create a narrative-following playlist. This tool is available at https://github.com/dylanashley/playlist-story-builder/releases/tag/v1.0.0...
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Automatic Embedding of Stories Into Collections of Independent Media
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TN_cdi_proquest_journals_2593343455
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2593343455
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2331-8422