thuiar/MMSA

Health v2 · maintenance only

Adoption not part of the score

1041 stars · 137 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

MMSA is a unified Python framework for multimodal sentiment analysis, supporting 15 MSA models and datasets like MOSI, MOSEI, and CH-SIMS. It offers both a Python API and command-line tool for training, testing, and benchmarking models with customizable multimodal features.

Use cases

• train and compare multimodal sentiment analysis models
• run sentiment experiments on MOSI MOSEI or CH-SIMS datasets
• benchmark MSA models in a unified framework
• tune hyperparameters for multimodal sentiment models
• extract custom multimodal features for sentiment analysis
• reproduce research results for multimodal sentiment models

When to choose

• you need a unified interface to train and compare multiple MSA models
• you want to experiment with standard multimodal sentiment datasets
• you need both Python API and CLI access for experiments
• you want reproducible baselines for multimodal sentiment research

When to avoid

• you need general-purpose sentiment analysis on plain text only
• you need production deployment of a sentiment model rather than research experimentation
• your data is not one of the supported multimodal formats

Facets

framework · maturity active

machine-learning nlp audio-processing cli machine-learning deep-learning data-science python cli windows multimodal-sentiment-analysis sentiment-analysis mosi mosei ch-sims research-framework pytorch natural-language-processing linux macos

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markdown · JSON · MCP: product_card(name="thuiar/MMSA")