loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Y. Priyadarshana ; Zilu Liang and Ian Piumarta

Affiliation: Kyoto University of Advanced Science (KUAS), Kyoto, Japan

Keyword(s): Multi-Party Written Discourse Analysis, Speaker Identification, Natural Language Processing.

Abstract: Multi-party conversation (MPC) analysis is a growing and challenging research area which involves multiple interlocutors and complex discourse structures among multiple utterances. Even though most of the existing methods consider implicit complicated structures in MPC modelling, much work remains to be done for speaker-centric written discourse parsing under MPC analysis. On the other hand, pre-trained language models (PLM) have achieved a significant success in utterance-interlocutor semantic modelling. In this study, we propose Who Says What (WSW), a novel PLM which models who says what in an MPC to understand equipping discourse parsing in deep semantic structures and contextualized representations of utterances and interlocutors. To our knowledge, this is the first attempt to use the relative semantic distance of utterances in MPCs to design self-supervised tasks for MPC utterance structure modelling and MPC utterance semantic modelling. Experiments on four public benchmark data sets show that our model outperforms the existing state-of-the-art MPC understanding baselines by considerable margins and achieves the new state-of-the-art performance in response utterance selection and speaker identification downstream tasks. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.145.64.210

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Priyadarshana, Y. ; Liang, Z. and Piumarta, I. (2023). Who Says What (WSW): A Novel Model for Utterance-Aware Speaker Identification in Text-Based Multi-Party Conversations. In Proceedings of the 19th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-672-9; ISSN 2184-3252, SciTePress, pages 26-36. DOI: 10.5220/0012164400003584

@conference{webist23,
author={Y. Priyadarshana and Zilu Liang and Ian Piumarta},
title={Who Says What (WSW): A Novel Model for Utterance-Aware Speaker Identification in Text-Based Multi-Party Conversations},
booktitle={Proceedings of the 19th International Conference on Web Information Systems and Technologies - WEBIST},
year={2023},
pages={26-36},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012164400003584},
isbn={978-989-758-672-9},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Web Information Systems and Technologies - WEBIST
TI - Who Says What (WSW): A Novel Model for Utterance-Aware Speaker Identification in Text-Based Multi-Party Conversations
SN - 978-989-758-672-9
IS - 2184-3252
AU - Priyadarshana, Y.
AU - Liang, Z.
AU - Piumarta, I.
PY - 2023
SP - 26
EP - 36
DO - 10.5220/0012164400003584
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic