SMC_CodecCLAP

This project explores the integration of Neural Audio Codecs (NACs) into Contrastive Language-Audio Pretraining (CLAP) models, demonstrating their superior feature discrimination and retrieval efficacy, and setting new benchmarks for audio representation in AI systems.

Setup Guide

We highly recommend users to run this project under conda environment.

Prepare the environment:

To create a new environment with the necessary dependencies, run the following command:

conda env create --name envname --file=env.yaml

DEMO Usage examples

DDP on Multi-GPU nodes

To run the project on multiple GPU nodes using Distributed Data Parallel (DDP), use the following command:

torchrun --nproc_per_node=4 SMC_CodecCLAP/retrieval/smc.py -c SMC_CodecCLAP/retrieval/settings/mel.yaml

CPU nodes

If you are running on CPU nodes, use the following command: