Papers with character understanding

2 papers
Multi-level Contrastive Learning for Script-based Character Understanding (2023.emnlp-main)

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Challenge: Scripts are written text for plays, movies, or broadcasts.
Approach: They propose a multi-level contrastive learning framework to capture characters’ global information in a fine-grained manner.
Outcome: The proposed framework improves on three character understanding sub-tasks by a considerable margin.
PACHAT: Persona-Aware Speech Assistant for Multi-party Dialogue (2025.emnlp-main)

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Challenge: Extensive research on spoken dialogue systems has advanced the development of intelligent voice assistants, but integration of role information within speech remains an underexplored area.
Approach: They propose a language-based spoken dialogue system that integrates role information within speech to generate contextually appropriate responses.
Outcome: The proposed architecture achieves speaker-specific responses, character understanding, and the generation of targeted replies in multi-party dialogue scenarios, surpassing existing spoken dialogue systems.

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