@inproceedings{labruna-magnini-2024-towards,
title = "Towards Cost-effective Multi-style Conversations: A Pilot Study in Task-oriented Dialogue Generation",
author = "Labruna, Tiziano and
Magnini, Bernardo",
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://preview.aclanthology.org/jlcl-multiple-ingestion/2024.lrec-main.1431/",
pages = "16473--16479",
abstract = "Conversations exhibit significant variation when different styles are employed by participants, often leading to subpar performance when a dialogue model is exclusively trained on single-style datasets. We present a cost-effective methodology for generating multi-style conversations, which can be used in the development of conversational agents. This methodology only assumes the availability of a conversational domain, such as a knowledge base, and leverages the generative capabilities of large language models. In a pilot study focused on the generation aspect of task-oriented dialogues, we extended the well-known MultiWOZ dataset to encompass multi-style variations. Our findings highlight two key experimental outcomes: (i) these novel resources pose challenges for current single-style models, and (ii) multi-style resources enhance the dialogue model`s resilience to stylistic variations."
}
Markdown (Informal)
[Towards Cost-effective Multi-style Conversations: A Pilot Study in Task-oriented Dialogue Generation](https://preview.aclanthology.org/jlcl-multiple-ingestion/2024.lrec-main.1431/) (Labruna & Magnini, LREC-COLING 2024)
ACL