MPDD-AVG: Multimodal Personality-Aware Depression Detection Data

A dataset for the MPDD-AVG Challenge at ACM MM 2026. It is designed for multimodal personality-aware depression detection via audio-visual interview and gait analysis. The dataset was created by author 'chasonfff' and was last updated on May 2, 2026.

Use Cases

• Train models for depression detection based on audio-visual interview data.
• Develop personality-aware AI systems based on multimodal behavioral cues.
• Benchmark gait analysis algorithms for mental health screening.

Strengths

• Dataset is associated with a formal academic challenge (MPDD-AVG Challenge @ ACM MM 2026).
• Focuses on a multimodal approach combining audio, visual, and gait data for a specific clinical task.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

huggingface

Freshness

Last updated 2026-05-02 06:12:54; freshness should be verified.