Paper

[redrabbit94]

Thanks for sharing, great work! Could you offer links to articles about this repo, and is it convenient to know if the repo contains the method you submitted in dcase 2022?

[wsntxxn]

1. The articles are provided. However, since I have reorganized the codes several times, the detailed step-to-step instruction is not included. For example, run_condition_adverse.py is for diversity-controllable captioning but the configuration files and the discriminator training scripts are missing. If you have problems with specific work, please contact me.
2. About DCASE 2022 submission, the contrastive pre-trained model is provided here. You can use this configuration and set the encoder argument pretrained as the path of the pre-trained model to train the base model. Reinforcement learning and ensemble codes will be uploaded later. However, I do not put the pre-training codes into this repo because it is independent. I will create another repo on audio-text retrieval involving contrastive pre-training.

[wsntxxn]

Sorry for the procrastination, the codes and sample configuration files for reinforcement learning and ensemble have been uploaded.

[wsntxxn]

The audio-text contrastive learning code has also been uploaded to https://github.com/wsntxxn/DCASE2022T6_CLAP. You can refer to it.

[redrabbit94]

Thanks so much！Best wishes！

发自我的iPhone

在 2023年2月16日，11:14，Xuenan Xu @.***> 写道：



The audio-text contrastive learning code has also been uploaded to https://github.com/wsntxxn/DCASE2022T6_CLAP. You can refer to it.

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