|
--- |
|
datasets: |
|
- facebook/multilingual_librispeech |
|
- yangwang825/audioset |
|
metrics: |
|
- accuracy |
|
pipeline_tag: audio-classification |
|
--- |
|
# SSAMBA: Self-Supervised Audio Mamba |
|
|
|
[![arXiv](https://img.shields.io/badge/arXiv-2405.11831-b31b1b.svg)](https://arxiv.org/abs/2405.11831) |
|
|
|
## 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 |
|
--- |