README.md

metadata

license: cc-by-nc-4.0
task_categories:
  - other
tags:
  - multimodal
  - personality-understanding
  - mbti
  - fairness

DMSP — Dataset for Multimodal Personality Research

The DMSP (Demographic-annotated Multimodal Student Personality) dataset is a resource designed to address the challenges in personality detection from multimodal content, particularly focusing on the Myers-Briggs Type Indicator (MBTI) and fairness evaluation.

Unlike existing datasets that rely heavily on text-only inputs, DMSP integrates Visual, Audio, and Textual modalities. By incorporating fairness attributes (Gender, Age, Race) and continuous soft labels, this dataset offers a more accurate reflection of how personality traits manifest in real-world scenarios.

• Paper: Debiased Multimodal Personality Understanding through Dual Causal Intervention
• GitHub Repository: Sabrina-han/DCAN

Key Features

• Multimodal Integration: Leverages CLIP (Visual), Wav2Clip (Audio), and CLIP Sentence Embeddings (Text) for robust feature representation.
• Fairness-Oriented: Includes demographic annotations (Gender, Age, Race) to facilitate fairness analysis and bias mitigation in AI models.
• Soft Labeling: Utilizes continuous scores for the 4 MBTI dimensions (E/I, N/S, F/T, J/P), moving beyond the limitations of hard binary classifications.

Dataset Structure

DMSP/
├── train.csv                 # Training labels and metadata
├── test.csv                  # Test labels and metadata
├── train_clipimage.pkl       # Visual features for training set (CLIP ViT-B/32)
├── test_clipimage.pkl        # Visual features for test set
├── train_audio_wav2clip.pkl  # Audio features for training set (Wav2Clip)
├── test_audio_wav2clip.pkl   # Audio features for test set
├── train_clipsentence.pkl    # Text features for training set (CLIP Sentence)
└── test_clipsentence.pkl     # Text features for test set

Sample Usage

You can load the dataset using the following snippet found in the official repository:

from train_FMPD_MBTI_baseline_fixed import DMSPDataset

train_ds = DMSPDataset(
    csv_file='DMSP/train.csv',
    data_dir='DMSP',
    split='train'
)

sample = train_ds[0]
print(sample.keys())
# Output: ['vid', 'mbti', 'demo', 'visual', 'audio', 'text']

Citation

If you use this dataset in your research, please cite:

@article{han2024debiased,
  title={Debiased Multimodal Personality Understanding through Dual Causal Intervention},
  author={Li, Han and others},
  journal={arXiv preprint arXiv:2605.06371},
  year={2024}
}