Audio Classification
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SSAMBA: Self-Supervised Audio Mamba

arXiv

Introduction

This repository contains the official implementation (in PyTorch) of the the paper SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model. SSAMBA is an advanced audio representation learning model designed to leverage self-supervised learning techniques using the Mamba State Space Model. This project builds on the success of the Self-Supervised Audio Spectrogram Transformer (SSAST) and introduces novel methodologies to further enhance performance and efficiency on various audio tasks.

Github: https://github.com/SiavashShams/ssamba


license: bsd-3-clause-clear

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Datasets used to train attentionisallyouneed369/ssamba