kyegomez/AudioMamba
Implementation of the paper: "Audio Mamba: Bidirectional State Space Model for Audio Representation Learning" in pytorch
Audio Mamba helps AI researchers and audio engineers develop advanced AI models that understand and process sound more effectively. It takes raw audio data and transforms it into rich representations, enabling AI to better interpret speech, music, and environmental sounds. This is primarily for those building cutting-edge audio AI applications.
Use this if you are an AI researcher or audio engineer looking to implement the latest state space models for superior audio representation learning in your AI projects.
Not ideal if you are looking for an off-the-shelf application to process audio without needing to build or train custom AI models.
Stars
14
Forks
1
Language
Shell
License
MIT
Category
Last pushed
Mar 09, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/kyegomez/AudioMamba"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
NVlabs/MambaVision
[CVPR 2025] Official PyTorch Implementation of MambaVision: A Hybrid Mamba-Transformer Vision Backbone
sign-language-translator/sign-language-translator
Python library & framework to build custom translators for the hearing-impaired and translate...
kyegomez/Jamba
PyTorch Implementation of Jamba: "Jamba: A Hybrid Transformer-Mamba Language Model"
autonomousvision/transfuser
[PAMI'23] TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving;...
kyegomez/MultiModalMamba
A novel implementation of fusing ViT with Mamba into a fast, agile, and high performance...