sony/sampleid
Code for the paper “Automatic Music Sample Identification with Multi-Track Contrastive Learning”.
This project helps music producers, DJs, and copyright holders automatically detect if a new song contains audio samples from existing music tracks. You input audio files of new compositions, and it identifies if any part originates from a reference database of existing music, providing details about the source material. It's designed for anyone needing to trace the lineage of sampled audio within musical works.
Use this if you need to quickly and accurately identify sampled content within new music tracks and trace them back to their original sources.
Not ideal if you are looking for a tool to generate new music or separate instruments within a track, as its primary function is sample identification.
Stars
19
Forks
2
Language
Python
License
MIT
Category
Last pushed
Jan 28, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/sony/sampleid"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
AdaptiveMotorControlLab/CEBRA
Learnable latent embeddings for joint behavioral and neural analysis - Official implementation of CEBRA
theolepage/sslsv
Toolkit for training and evaluating Self-Supervised Learning (SSL) frameworks for Speaker...
PaddlePaddle/PASSL
PASSL包含 SimCLR,MoCo v1/v2,BYOL,CLIP,PixPro,simsiam, SwAV, BEiT,MAE 等图像自监督算法以及 Vision...
YGZWQZD/LAMDA-SSL
30 Semi-Supervised Learning Algorithms
ModSSC/ModSSC
ModSSC: A Modular Framework for Semi Supervised Classification