AuTGeLy: Automatic Title Generator based on Song Lyrics Extractions

Diego Vallejo-Huanga, Esteban Carrera, Jonathan Manay

Producción científica: Capítulo del libro/informe/acta de congresoContribución de conferenciarevisión exhaustiva

Resumen

Natural Language Processing (NLP) is one of the most popular fields of Artificial Intelligence and its applications are diverse. This article presents a recommender system, through a web application, that extracts the lyrics of a song entered in audio format and uses NLP techniques to process the textual corpus of the lyrics and recommend a title for the song. The level of effectiveness of the system was analyzed, measuring the percentage of similarity between the ground truth, which is the original title of the song, and our recommendation. For the experiments, a dataset of 30 songs was used divided into three taxonomies, small, medium, and large, that change according to the length of tokens of the original title. The results show an accuracy of 70% for small titles and 20% for medium and long titles. It is also shown that the web tool is enabled to formulate control of lexical content in songs since it does not use the original title of the song as input.

Idioma originalInglés
Título de la publicación alojadaProceedings - 20th IEEE International Conference on Machine Learning and Applications, ICMLA 2021
EditoresM. Arif Wani, Ishwar K. Sethi, Weisong Shi, Guangzhi Qu, Daniela Stan Raicu, Ruoming Jin
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas1588-1593
Número de páginas6
ISBN (versión digital)9781665443371
DOI
EstadoPublicada - 2021
Evento20th IEEE International Conference on Machine Learning and Applications, ICMLA 2021 - Virtual, Online, Estados Unidos
Duración: 13 dic. 202116 dic. 2021

Serie de la publicación

NombreProceedings - 20th IEEE International Conference on Machine Learning and Applications, ICMLA 2021

Conferencia

Conferencia20th IEEE International Conference on Machine Learning and Applications, ICMLA 2021
País/TerritorioEstados Unidos
CiudadVirtual, Online
Período13/12/2116/12/21

Nota bibliográfica

Publisher Copyright:
© 2021 IEEE.

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