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YAML Metadata
Warning:
The task_categories "classification" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
YAML Metadata
Warning:
The task_categories "Depression detection" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
AVDD-TCMI Dataset
Introduction
The AVDD-TCMI dataset is a multimodal dataset for depression detection. Our dataset comprises a total of 1,230 valid samples, including 969 non-depressed individuals and 261 depressed individuals. It contains two primary subsets:
- HDS (Hospital Depression Subset): HDS is collected from volunteers at West China Hospital of Sichuan University and includes 282 valid samples, comprising 159 non-depressed volunteers (including doctors, nurses, and patients without depression) and 123 clinically diagnosed depressed patients undergoing treatments.
- SDS (Student Depression Subset): SDS is collected from a middle school and contains 948 valid samples, including 810 non-depressed and 138 depressed volunteer students.
Modalities
- mulitimodal
- audio
- visual
Structure
AVDD-TCMI-dataset/
├── HDS/
│ ├── 0/
│ │ ├── 0_tcm/ # regional features extracted based on TCM facial inspection (images)
│ │ ├── 0_acoustic.csv # audio_features
│ │ └── 0_visual.csv # video_features
│ └── ...
├── SDS/
│ └── 0/
│ └── ...
├── HDS_labels.csv # id,label (0=non-depressed,1=depressed),gender (f=female,m=male)
└── SDS_labels.csv
Data Splits
This dataset is not pre-split into train/validation/test. Users should perform their own split.
Contact
For questions, contact:[email protected]
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