MDPEdataset nielsr HF Staff commited on
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Add task categories and link to Github repo (#4)

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- Add task categories and link to Github repo (992fe116a3629c40e3c6ece64e2a51f0d7a06856)


Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

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  1. README.md +8 -7
README.md CHANGED
@@ -1,20 +1,23 @@
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  ---
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- license: cc-by-nc-sa-4.0
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  language:
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  - zh
 
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  size_categories:
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  - 100B<n<1T
 
 
 
 
 
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  ---
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-
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  # MDPE Dataset
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  MDPE is a multimodal deception dataset. Besides deception features, it also includes individual differences information in personality and emotional expression characteristics. MDPE not only supports deception detection, but also provides conditions for tasks such as personality recognition and emotion recognition, and can even study the relationships between them.
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-
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  ## Dataset Download
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-
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  The data are passcode protected. Please download and send the signed [EULA](https://drive.google.com/file/d/1A1F8szMOTf9-rK8DYD23GruBArtnYdLl/view?usp=sharing) to [mdpe.contact@gmail.com](mdpe.contact@gmail.com) for access request.
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  ## Citation
@@ -30,6 +33,4 @@ Please cite our paper if you find our work useful for your research:
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  journal={arXiv preprint arXiv:2407.12274},
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  year={2024}
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  }
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- ```
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-
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-
 
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  ---
 
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  language:
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  - zh
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+ license: cc-by-nc-sa-4.0
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  size_categories:
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  - 100B<n<1T
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+ task_categories:
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+ - video-classification
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+ - deception-detection
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+ - personality-recognition
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+ - emotion-recognition
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  ---
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  # MDPE Dataset
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  MDPE is a multimodal deception dataset. Besides deception features, it also includes individual differences information in personality and emotional expression characteristics. MDPE not only supports deception detection, but also provides conditions for tasks such as personality recognition and emotion recognition, and can even study the relationships between them.
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+ [Github Repo](https://github.com/MDPEdataset/MDPE)
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  ## Dataset Download
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  The data are passcode protected. Please download and send the signed [EULA](https://drive.google.com/file/d/1A1F8szMOTf9-rK8DYD23GruBArtnYdLl/view?usp=sharing) to [mdpe.contact@gmail.com](mdpe.contact@gmail.com) for access request.
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  ## Citation
 
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  journal={arXiv preprint arXiv:2407.12274},
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  year={2024}
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  }
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+ ```