English

AllWOZ: Towards Multilingual Task-Oriented Dialog Systems for All

Computation and Language 2021-12-16 v1

Abstract

A commonly observed problem of the state-of-the-art natural language technologies, such as Amazon Alexa and Apple Siri, is that their services do not extend to most developing countries' citizens due to language barriers. Such populations suffer due to the lack of available resources in their languages to build NLP products. This paper presents AllWOZ, a multilingual multi-domain task-oriented customer service dialog dataset covering eight languages: English, Mandarin, Korean, Vietnamese, Hindi, French, Portuguese, and Thai. Furthermore, we create a benchmark for our multilingual dataset by applying mT5 with meta-learning.

Keywords

Cite

@article{arxiv.2112.08333,
  title  = {AllWOZ: Towards Multilingual Task-Oriented Dialog Systems for All},
  author = {Lei Zuo and Kun Qian and Bowen Yang and Zhou Yu},
  journal= {arXiv preprint arXiv:2112.08333},
  year   = {2021}
}
R2 v1 2026-06-24T08:18:58.864Z