@inproceedings{gao-etal-2025-interaction,
title = "Interaction Matters: An Evaluation Framework for Interactive Dialogue Assessment on {E}nglish Second Language Conversations",
author = "Gao, Rena and
Roever, Carsten and
Lau, Jey Han",
editor = "Rambow, Owen and
Wanner, Leo and
Apidianaki, Marianna and
Al-Khalifa, Hend and
Eugenio, Barbara Di and
Schockaert, Steven",
booktitle = "Proceedings of the 31st International Conference on Computational Linguistics",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.coling-main.729/",
pages = "10977--11012",
abstract = "We present an evaluation framework for interactive dialogue assessment in the context of English as a Second Language (ESL) speakers. Our framework collects dialogue-level interactivity labels (e.g., topic management; 4 labels in total) and micro-level span features (e.g., backchannels; 17 features in total). Given our annotated data, we study how the micro-level features influence the (higher level) interactivity quality of ESL dialogues by constructing various machine learning-based models. Our results demonstrate that certain micro-level features strongly correlate with interactivity quality, like reference words (e.g., she, her, he), revealing new insights about the interaction between higher-level dialogue quality and lower-level fundamental linguistic signals. Our framework also provides a means to assess ESL communication, which is useful for language assessment."
}
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%0 Conference Proceedings
%T Interaction Matters: An Evaluation Framework for Interactive Dialogue Assessment on English Second Language Conversations
%A Gao, Rena
%A Roever, Carsten
%A Lau, Jey Han
%Y Rambow, Owen
%Y Wanner, Leo
%Y Apidianaki, Marianna
%Y Al-Khalifa, Hend
%Y Eugenio, Barbara Di
%Y Schockaert, Steven
%S Proceedings of the 31st International Conference on Computational Linguistics
%D 2025
%8 January
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F gao-etal-2025-interaction
%X We present an evaluation framework for interactive dialogue assessment in the context of English as a Second Language (ESL) speakers. Our framework collects dialogue-level interactivity labels (e.g., topic management; 4 labels in total) and micro-level span features (e.g., backchannels; 17 features in total). Given our annotated data, we study how the micro-level features influence the (higher level) interactivity quality of ESL dialogues by constructing various machine learning-based models. Our results demonstrate that certain micro-level features strongly correlate with interactivity quality, like reference words (e.g., she, her, he), revealing new insights about the interaction between higher-level dialogue quality and lower-level fundamental linguistic signals. Our framework also provides a means to assess ESL communication, which is useful for language assessment.
%U https://aclanthology.org/2025.coling-main.729/
%P 10977-11012
Markdown (Informal)
[Interaction Matters: An Evaluation Framework for Interactive Dialogue Assessment on English Second Language Conversations](https://aclanthology.org/2025.coling-main.729/) (Gao et al., COLING 2025)
ACL