MEIJU - The 1st Multimodal Emotion and Intent Joint Understanding Challenge

Multimodal Emotion and Intent Joint Understanding (MEIJU) aims to decode the semantic information expressed in the multimodal dialogues while inferring the emotions and intents, providing users with a more humanized human-machine interaction experience. However, challenges such as difficulties in data acquisition and imbalance annotations have made it difficult for current methods to meet the demands of practical applications. Therefore, we have organized two tracks focusing on the key themes of semi-supervised learning and class imbalance. Additionally, we have prepared data in two different languages (English and Mandarin) for each track, treating each language as a sub-track, to encourage participants to explore solutions in more diverse linguistic environments. Our code can be found at https://github.com/AI-S2-Lab/MEIJU2025-baseline.