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

In this paper, we introduce the Akan Conversation Emotion (AkaCE) 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.AkaCE, 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 AkaCE through experiments using state-of-the-art emotion recognition methods, establishing solid baselines for future research.We hope AkaCE inspires further work on inclusive, linguistically and culturally diverse NLP resources.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.findings-acl.510
Citations
1
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
2.12

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article

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

Natalie Schluter, Julia Hirschberg, Lin Ai, Robert Chen et al.
1 citations
Emotion and Mood Recognition
2.12
article

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

Natalie Schluter, Julia Hirschberg, Lin Ai, Robert Chen, Zehui Wu, Pengyuan Shi, Ziwei Gong, David Sasu
article en
1 citations

Abstract

In this paper, we introduce the Akan Conversation Emotion (AkaCE) 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.AkaCE, 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 AkaCE through experiments using state-of-the-art emotion recognition methods, establishing solid baselines for future research.We hope AkaCE inspires further work on inclusive, linguistically and culturally diverse NLP resources.

National Science Foundation, Defense Advanced Research Projects Agency, Advanced Research Projects Agency
Openalex Percentile: Top 12%
Emotion and Mood Recognition
2.12
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