Home Projects MELD
MELD
Python

MELD

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation

by declare-lab · GitHub
Stars
Forks
License
Created
Last commit
Category
Language
chatbotconversational-aidialogueGPL-3.0Python
View on GitHub
In plain words

Segment objects in images and videos using advanced deep learning techniques with a Python library.

You maintain this project?

Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.

Claim this page →
MELD — GitHub preview card
📈 Star history
1 0721 071
2026-07-202026-08-31
📈 Track MELD

Get an email alert on its next release or when it starts trending — never miss the moment.

Free · no card · unsubscribe anytime
Get email alerts →
📄 About

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation

MELD has 1.1k stars on GitHub. It has been forked 234 times. MELD is written mainly in Python. It has been in active development since 2018. MELD is available under the GPL-3.0 license. Its main topics are chatbot, conversational-ai, dialogue, dialogue-systems.

Frequently asked questions

What is MELD?

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation

Is MELD open source?

MELD is an open-source project. It is released under the GPL-3.0 license.

Is MELD free?

Yes. MELD is free and open source — you can use, modify and self-host it. Its GPL-3.0 license is copyleft: if you distribute a modified version, it must remain under the same license.

What license does MELD use?

MELD is available under the GPL-3.0 license.

What language is MELD written in?

MELD is written mainly in Python.

🏅 Maintainer of this project?
olud.ai badge — MELD

Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.

[![olud.ai](https://olud.ai/badge.php?tool=declare-lab-meld)](https://olud.ai/project/declare-lab-meld.html)
More badge options →
🧬 Shares DNA with🧬 View the DNA map →

Measured from GitHub topics shared by both projects, weighted by how rare each topic is.