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Bibliographic Details
Main Authors: Yuan, Chunyu, Devaney, Johanna
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.02101
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author Yuan, Chunyu
Devaney, Johanna
author_facet Yuan, Chunyu
Devaney, Johanna
contents In this work, we propose a new efficient solution, which is a Mamba-based model named BMACE (Bidirectional Mamba-based network, for Automatic Chord Estimation), which utilizes selective structured state-space models in a bidirectional Mamba layer to effectively model temporal dependencies. Our model achieves high prediction performance comparable to state-of-the-art models, with the advantage of requiring fewer parameters and lower computational resources
format Preprint
id arxiv_https___arxiv_org_abs_2601_02101
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Mamba-Based Model for Automatic Chord Recognition
Yuan, Chunyu
Devaney, Johanna
Sound
In this work, we propose a new efficient solution, which is a Mamba-based model named BMACE (Bidirectional Mamba-based network, for Automatic Chord Estimation), which utilizes selective structured state-space models in a bidirectional Mamba layer to effectively model temporal dependencies. Our model achieves high prediction performance comparable to state-of-the-art models, with the advantage of requiring fewer parameters and lower computational resources
title A Mamba-Based Model for Automatic Chord Recognition
topic Sound
url https://arxiv.org/abs/2601.02101