RCL_FS_BSED

KO | EN

gitlite — search

#javascript #hacktoberfest #ai #typescript #llm #golang #machine-learning #linux #java #awesome #cli #awesome-list #ios #mcp

(★ 9)

Regularized Contrastive Learning for Few-shot Bioacoustic Sound Event Detection (ICASSP 2024)

RCL_FS_BSED 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Regularized Contrastive Learning for Few-shot Bioacoustic Sound Event Detection
Authors: Ilyass Moummad, Romain Serizel, Nicolas Farrugia
---

This is the implementation of our [paper](https://arxiv.org/abs/2309.08971) accepted at ICASSP 2024\
We improve over our previous [work](https://github.com/ilyassmoummad/dcase23_task5_scl) that ranked 2nd in the [DCASE 2023 Challenge Task5](https://dcase.community/challenge2023/task-few-shot-bioacoustic-event-detection-results) by adding a regularization term to the training loss, and by improving the inference strategy

```args.py```: contains default values for arguments

## Data
Download the dataset from Zenodo: https://zenodo.org/records/6482837
To create the spectrograms of the training set:\
```create_train.py```: with argument ```--traindir``` for the folder containing the training datasets

## Training
To train the feature extractor:\
```train.py```: with arguments ```--traindir``` (the same as above)
```--method```: optional argument for the pretraining method ```scl``` for SupCon and ```ssl``` for SimCLR

## Evaluation
To evaluate using finetuning:\
```eval_finetune```: with arguments ```--valdir``` for the folder containing the validation datasets\
To evaluate without finetuning (for faster inference):\
```eval_nofinetune```: with arguments ```--valdir``` for the folder containing the validation datasets

To get the scores:\
```evaluation.py``` : with arguments ```--pred_file``` for the predictions csv file created by the eval script (the file is in : traindir/../../outputs/eval.csv'), ```--ref_files``` for the path of validation datasets (same as ```--valdir```), and ```--save_path``` for the folder where to save the json file containing the scores

If you any question or a problem with the code/results do not hesitate to mail me on : ilyass.moummad@imt-atlantique.fr or open an issue on this repository, I am very responsive.

---
### To cite our paper
```
@misc{moummad2023regularized,
      title={Regularized Contrastive Pre-training for Few-shot Bioacoustic Sound Detection}, 
      author={Ilyass Moummad and Romain Serizel and Nicolas Farrugia},
      year={2023},
      eprint={2309.08971},
      archivePrefix={arXiv},
      primaryClass={cs.SD}
}
```

RCL_FS_BSED

RCL_FS_BSED 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

RCL_FS_BSED

RCL_FS_BSED 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README