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GhostWriter: Using an LSTM for Automatic Rap Lyric Generation

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This paper demonstrates the effectiveness of a Long Short-Term Memory language model in our initial efforts to generate unconstrained rap lyrics. The goal of this model is to generate lyrics that are similar in style to that of a given rapper, but not identical to existing lyrics: this is the task of ghostwriting. Unlike previous work, which defines explicit templates for lyric generation, our model defines its own rhyme scheme, line length, and verse length. Our experiments show that a Long Short-Term Memory language model produces better "ghostwritten" lyrics than a baseline model.

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Publication details

DOI
10.18653/v1/d15-1221
OpenAlex
W2250842199
Document type
conference-paper
Language
EN
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