@inproceedings{mahajan-shaikh-2024-persona-aware,
title = "Persona-aware Multi-party Conversation Response Generation",
author = "Mahajan, Khyati and
Shaikh, Samira",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.1113",
pages = "12712--12723",
abstract = "Modeling interlocutor information is essential towards modeling multi-party conversations to account for the presence of multiple participants. We investigate the role of including the persona attributes of both the speaker and addressee relevant to each utterance, collected via 3 distinct mock social media experiments. The participants were recruited via MTurk, and were unaware of the persona attributes of the other users they interacted with on the platform. Our main contributions include 1) a multi-party conversation dataset with rich associated metadata (including persona), and 2) a persona-aware heterogeneous graph transformer response generation model. We find that PersonaHeterMPC provides a good baseline towards persona-aware generation for multi-party conversation modeling, generating responses which are relevant and consistent with the interlocutor personas relevant to the conversation.",
}
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<abstract>Modeling interlocutor information is essential towards modeling multi-party conversations to account for the presence of multiple participants. We investigate the role of including the persona attributes of both the speaker and addressee relevant to each utterance, collected via 3 distinct mock social media experiments. The participants were recruited via MTurk, and were unaware of the persona attributes of the other users they interacted with on the platform. Our main contributions include 1) a multi-party conversation dataset with rich associated metadata (including persona), and 2) a persona-aware heterogeneous graph transformer response generation model. We find that PersonaHeterMPC provides a good baseline towards persona-aware generation for multi-party conversation modeling, generating responses which are relevant and consistent with the interlocutor personas relevant to the conversation.</abstract>
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%0 Conference Proceedings
%T Persona-aware Multi-party Conversation Response Generation
%A Mahajan, Khyati
%A Shaikh, Samira
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F mahajan-shaikh-2024-persona-aware
%X Modeling interlocutor information is essential towards modeling multi-party conversations to account for the presence of multiple participants. We investigate the role of including the persona attributes of both the speaker and addressee relevant to each utterance, collected via 3 distinct mock social media experiments. The participants were recruited via MTurk, and were unaware of the persona attributes of the other users they interacted with on the platform. Our main contributions include 1) a multi-party conversation dataset with rich associated metadata (including persona), and 2) a persona-aware heterogeneous graph transformer response generation model. We find that PersonaHeterMPC provides a good baseline towards persona-aware generation for multi-party conversation modeling, generating responses which are relevant and consistent with the interlocutor personas relevant to the conversation.
%U https://aclanthology.org/2024.lrec-main.1113
%P 12712-12723
Markdown (Informal)
[Persona-aware Multi-party Conversation Response Generation](https://aclanthology.org/2024.lrec-main.1113) (Mahajan & Shaikh, LREC-COLING 2024)
ACL
- Khyati Mahajan and Samira Shaikh. 2024. Persona-aware Multi-party Conversation Response Generation. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 12712–12723, Torino, Italia. ELRA and ICCL.