Visualizing Similarities between American Rap-Artists

+Visualization+application+domains%22&type=SU">CCS Concepts: Human-centered computing --> Visualization application domains, Visualization systems and tools, Applied computing --> Sound and music computing, Document management and text processing, Sound and music computing, Applied computing, Human centered computing -->

Popis:	Rap music is one of the biggest music genres in the world today. Since the early days of rap music, references not only to pop culture but also to other rap artists have been an integral part of the lyrics' artistry. In addition, rap musicians reference each other by adopting fragments of lyrics, for example, to give credit. This kind of text reuse can be used to create connections between individual artists. Due to the large amount of lyrics, only automated detection methods can efficiently detect similarities between the songs and the artists. Here, we present a visualization system for analyzing rap music lyrics. We also trained a network tailored specifically for rap lyrics to compute similarities in lyrics. Here a video of the prototype can be seen. Posters Christofer Meinecke, Jeremias Schebera, Jakob Eschrich, and Daniel Wiegreffe
DOI:	10.2312/evp.20221129
Přístupová URL adresa:	https://explore.openaire.eu/search/publication?articleId=doi_________::c23281a6b883513238fcb07bd0ea0bfa
Přírůstkové číslo:	edsair.doi...........c23281a6b883513238fcb07bd0ea0bfa
Autor:	Meinecke, Christofer, Schebera, Jeremias, Eschrich, Jakob, Wiegreffe, Daniel
Rok vydání:	2022
Předmět:	Visualization application domains CCS Concepts: Human-centered computing --> Visualization application domains Visualization systems and tools Applied computing --> Sound and music computing Document management and text processing Sound and music computing Applied computing Human centered computing
DOI:	10.2312/evp.20221129
Popis:	Rap music is one of the biggest music genres in the world today. Since the early days of rap music, references not only to pop culture but also to other rap artists have been an integral part of the lyrics' artistry. In addition, rap musicians reference each other by adopting fragments of lyrics, for example, to give credit. This kind of text reuse can be used to create connections between individual artists. Due to the large amount of lyrics, only automated detection methods can efficiently detect similarities between the songs and the artists. Here, we present a visualization system for analyzing rap music lyrics. We also trained a network tailored specifically for rap lyrics to compute similarities in lyrics. Here a video of the prototype can be seen. Posters Christofer Meinecke, Jeremias Schebera, Jakob Eschrich, and Daniel Wiegreffe
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c23281a6b883513238fcb07bd0ea0bfa Zobrazit plný text záznamu