Title
Neural network assisted composition for piano in jazz
Author
Ismael Medina Muñoz
Contributor
Elio Atenógenes Villaseñor García (Collaborator)
Access level
Open Access
Subjects
Summary or description
Artificial Intelligence has taken an important role in activities that were once considered exclusively human. Generative AI is a vibrant area of research, with increasing interest in application fields related to the arts. The recent plethora of innovations in fields like visual arts and natural language processing, which are able to engage in dialogue with users, are just two examples of commercial applications that are driving innovation research for big tech giants. It would not be untrue to say that these innovations are shaping mankind’s development.
Music is an investigative field that presents a challenge. Musical theory itself is challenging for humans, and music is as diverse and rich as the cultures in which it has evolved. This research and proposal is intended as a novel approach to creating a generative artificial intelligence that assists in piano composition for jazz tunes. This genre was selected because of the challenge that its richness and complexity for musical execution and interpretation pose.
By using a Recurrent Neural Net to create new sequences of n-notes from an initial n-note set and using a probabilistic approach to set the duration of each note in the produced n-notes set, the generative artificial intelligence described in this document is the piano composer assistant for jazz tunes.
Publisher
INFOTEC Centro de Investigación e Innovación en Tecnologías de la Información y Comunicación
Publish date
February, 2023
Publication type
Master thesis
Publication version
Published Version
Information Resource
Format
application/pdf
Language
English
Audience
Students
Researchers
General public
Citation suggestion
Medina Muñoz, Ismael. (2023). Neural network assisted composition for piano in jazz. [Propuesta de Intervención, INFOTEC].
Source repository
Repositorio Institucional de INFOTEC
Downloads
43