Abstract
Machine Translation (MT)-empowered chatbots are not established yet, however, we see an amazing future breaking language barriers and enabling conversation in multiple languages without time-consuming language model building and training, particularly for under-resourced languages. In this paper we focus on the under-resourced Luxembourgish language. This article describes the experiments we have done with a dataset containing administrative questions that we have manually created to offer BERT QA capabilities to a multilingual chatbot. The chatbot supports visual dialog flow diagram creation (through an interface called BotStudio) in which a dialog node manages the user question at a specific step. Dialog nodes can be matched to the user’s question by using a BERT classification model which labels the question with a dialog node label.- Anthology ID:
- 2022.sigul-1.27
- Volume:
- Proceedings of the 1st Annual Meeting of the ELRA/ISCA Special Interest Group on Under-Resourced Languages
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Maite Melero, Sakriani Sakti, Claudia Soria
- Venue:
- SIGUL
- SIG:
- SIGUL
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 207–212
- Language:
- URL:
- https://aclanthology.org/2022.sigul-1.27
- DOI:
- Cite (ACL):
- Dimitra Anastasiou. 2022. ENRICH4ALL: A First Luxembourgish BERT Model for a Multilingual Chatbot. In Proceedings of the 1st Annual Meeting of the ELRA/ISCA Special Interest Group on Under-Resourced Languages, pages 207–212, Marseille, France. European Language Resources Association.
- Cite (Informal):
- ENRICH4ALL: A First Luxembourgish BERT Model for a Multilingual Chatbot (Anastasiou, SIGUL 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2022.sigul-1.27.pdf