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

翻译：本研究提出了一种新的高效解决方案，即基于Mamba的模型BMACE（双向Mamba网络，用于自动和弦估计）。该模型在双向Mamba层中利用选择性结构化状态空间模型，以有效建模时间依赖性。我们的模型实现了与最先进模型相当的高预测性能，同时具有参数更少、计算资源需求更低的优势。