@inproceedings{tsunomori-etal-2026-felt,
title = "From Felt Sense to Words: Construction and Analysis of a Focusing Dialogue Dataset for Verbalization",
author = "Tsunomori, Yuiko and
Chiba, Yuya and
Koshikawa, Yosuke",
editor = "Choi, Jinho D. and
Chen, Yun-Nung and
Funakoshi, Kotaro and
Emami, Ali",
booktitle = "Proceedings of the 27th Annual Meeting of the Special Interest Group on Discourse and Dialogue",
month = aug,
year = "2026",
address = "Atlanta, Georgia, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.sigdial-1.19/",
pages = "258--270",
abstract = "Verbalization, the process of expressing one{'}s internal states in words, has been shown to deepen self-understanding and improve well-being. However, this can be difficult to achieve for some individuals. One approach to supporting verbalization is Focusing-Oriented Psychotherapy. Focusing facilitates verbalization by guiding a speaker{'}s attention to their felt sense, an internal state that has not yet been verbalized, and helping them to find the words that appropriately express this felt sense through dialogue. Toward developing Focusing dialogue systems that support user verbalization, we constructed a dataset containing Focusing dialogues between professionally trained listeners and speakers. This dataset consists of 50 dialogues (762 minutes, 17,986 utterances) and contains ratings of verbalization progress, subjective evaluations, and dialogue act (DA) annotations. To clarify the characteristics of Focusing dialogues, we analyzed associations among verbalization progress, subjective evaluations, and DA usage. Based on these analyses, we discussed design implications for Focusing dialogue systems."
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<abstract>Verbalization, the process of expressing one’s internal states in words, has been shown to deepen self-understanding and improve well-being. However, this can be difficult to achieve for some individuals. One approach to supporting verbalization is Focusing-Oriented Psychotherapy. Focusing facilitates verbalization by guiding a speaker’s attention to their felt sense, an internal state that has not yet been verbalized, and helping them to find the words that appropriately express this felt sense through dialogue. Toward developing Focusing dialogue systems that support user verbalization, we constructed a dataset containing Focusing dialogues between professionally trained listeners and speakers. This dataset consists of 50 dialogues (762 minutes, 17,986 utterances) and contains ratings of verbalization progress, subjective evaluations, and dialogue act (DA) annotations. To clarify the characteristics of Focusing dialogues, we analyzed associations among verbalization progress, subjective evaluations, and DA usage. Based on these analyses, we discussed design implications for Focusing dialogue systems.</abstract>
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%0 Conference Proceedings
%T From Felt Sense to Words: Construction and Analysis of a Focusing Dialogue Dataset for Verbalization
%A Tsunomori, Yuiko
%A Chiba, Yuya
%A Koshikawa, Yosuke
%Y Choi, Jinho D.
%Y Chen, Yun-Nung
%Y Funakoshi, Kotaro
%Y Emami, Ali
%S Proceedings of the 27th Annual Meeting of the Special Interest Group on Discourse and Dialogue
%D 2026
%8 August
%I Association for Computational Linguistics
%C Atlanta, Georgia, USA
%F tsunomori-etal-2026-felt
%X Verbalization, the process of expressing one’s internal states in words, has been shown to deepen self-understanding and improve well-being. However, this can be difficult to achieve for some individuals. One approach to supporting verbalization is Focusing-Oriented Psychotherapy. Focusing facilitates verbalization by guiding a speaker’s attention to their felt sense, an internal state that has not yet been verbalized, and helping them to find the words that appropriately express this felt sense through dialogue. Toward developing Focusing dialogue systems that support user verbalization, we constructed a dataset containing Focusing dialogues between professionally trained listeners and speakers. This dataset consists of 50 dialogues (762 minutes, 17,986 utterances) and contains ratings of verbalization progress, subjective evaluations, and dialogue act (DA) annotations. To clarify the characteristics of Focusing dialogues, we analyzed associations among verbalization progress, subjective evaluations, and DA usage. Based on these analyses, we discussed design implications for Focusing dialogue systems.
%U https://aclanthology.org/2026.sigdial-1.19/
%P 258-270
Markdown (Informal)
[From Felt Sense to Words: Construction and Analysis of a Focusing Dialogue Dataset for Verbalization](https://aclanthology.org/2026.sigdial-1.19/) (Tsunomori et al., SIGDIAL 2026)
ACL