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The Deep Learning Revolution in MIR: The Pros and Cons, the Needs and the Challenges Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Generating Walking Bass Lines with HMM

Authors : Ayumi Shiga, Tetsuro Kitahara

Published in: Perception, Representations, Image, Sound, Music

Publisher: Springer International Publishing

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Abstract

In this paper, we propose a method of generating walking bass lines for jazz with a hidden Markov model (HMM). Although automatic harmonization has been widely and actively studied, automatic generation of walking bass lines has not. With our model, which includes hidden states that represent combinations of pitch classes and metric positions, different distributions of bass notes selected at different metric positions can be learned. The results of objective and subjective evaluations suggest that the model can learn such different tendencies of bass notes at different metric positions and generates musically flowing bass lines that contain passing notes.

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previous chapter Musical Note Attacks Description in Reverberant Environments
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Metadata
Title
Generating Walking Bass Lines with HMM
Authors
Ayumi Shiga
Tetsuro Kitahara
Copyright Year
2021
Book
Perception, Representations, Image, Sound, Music

Print ISBN: 978-3-030-70209-0

Electronic ISBN: 978-3-030-70210-6

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-70210-6_17