Akan Cinematic Emotions (ACE): A Multimodal Multi-party Dataset for Emotion Recognition in Movie Dialogues

TL;DR

The paper introduces ACE, a pioneering multimodal emotion recognition dataset for the Akan language, featuring dialogues with audio, visual, and textual data, along with prosodic annotations, to advance inclusive NLP research.

Contribution

It presents the first African-language multimodal emotion dataset with prosodic annotations, filling a resource gap for low-resource languages in emotion recognition.

Findings

ACE dataset contains 385 dialogues and 6,162 utterances.

State-of-the-art methods establish baseline performance on ACE.

The dataset supports multimodal and prosodic emotion analysis.

Abstract

In this paper, we introduce the Akan Conversation Emotion (ACE) dataset, the first multimodal emotion dialogue dataset for an African language, addressing the significant lack of resources for low-resource languages in emotion recognition research. ACE, developed for the Akan language, contains 385 emotion-labeled dialogues and 6,162 utterances across audio, visual, and textual modalities, along with word-level prosodic prominence annotations. The presence of prosodic labels in this dataset also makes it the first prosodically annotated African language dataset. We demonstrate the quality and utility of ACE through experiments using state-of-the-art emotion recognition methods, establishing solid baselines for future research. We hope ACE inspires further work on inclusive, linguistically and culturally diverse NLP resources.