  Emotion recognition in conversations is a challenging task that has recently
gained popularity due to its potential applications. Until now, however, a
large-scale multimodal multi-party emotional conversational database containing
more than two speakers per dialogue was missing. Thus, we propose the
Multimodal EmotionLines Dataset (MELD), an extension and enhancement of
EmotionLines. MELD contains about 13,000 utterances from 1,433 dialogues from
the TV-series Friends. Each utterance is annotated with emotion and sentiment
labels, and encompasses audio, visual and textual modalities. We propose
several strong multimodal baselines and show the importance of contextual and
multimodal information for emotion recognition in conversations. The full
dataset is available for use at http:// affective-meld.github.io.
