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Neural network assisted composition for piano in jazz
Ismael Medina Muñoz
Elio Atenógenes Villaseñor García
Acceso Abierto
Atribución-NoComercial-CompartirIgual
Inteligencia Artificial
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.
INFOTEC Centro de Investigación e Innovación en Tecnologías de la Información y Comunicación
2023-02
Tesis de maestría
Inglés
Estudiantes
Investigadores
Público en general
Medina Muñoz, Ismael. (2023). Neural network assisted composition for piano in jazz. [Propuesta de Intervención, INFOTEC].
DISPOSITIVOS DE GRABACIÓN
Versión publicada
publishedVersion - Versión publicada
Aparece en las colecciones: Maestría en Ciencia de Datos e Información

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