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Comparing MultiLingual and Multiple MonoLingual Models for Intent Classification and Slot Filling
Lothritz, Cedric; Allix, Kevin; Lebichot, Bertrand et al.
2021In 26th International Conference on Applications of Natural Language to Information Systems
Peer reviewed
 

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Keywords :
Chatbots; Multilingualism; Intent Classification; Slot Filling
Abstract :
[en] With the momentum of conversational AI for enhancing client-to-business interactions, chatbots are sought in various domains, including FinTech where they can automatically handle requests for opening/closing bank accounts or issuing/terminating credit cards. Since they are expected to replace emails and phone calls, chatbots must be capable to deal with diversities of client populations. In this work, we focus on the variety of languages, in particular in multilingual countries. Specifically, we investigate the strategies for training deep learning models of chatbots with multilingual data. We perform experiments for the specific tasks of Intent Classification and Slot Filling in financial domain chatbots and assess the performance of mBERT multilingual model vs multiple monolingual models.
Disciplines :
Computer science
Author, co-author :
Lothritz, Cedric  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX
Allix, Kevin ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX
Lebichot, Bertrand ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX
Veiber, Lisa ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX
Bissyande, Tegawendé François D Assise  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX
Klein, Jacques ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX
External co-authors :
no
Language :
English
Title :
Comparing MultiLingual and Multiple MonoLingual Models for Intent Classification and Slot Filling
Publication date :
25 June 2021
Event name :
NLDB2021: 26th International Conference on Natural Language & Information Systems
Event date :
from 23-06-2021 to 25-05-2021
Main work title :
26th International Conference on Applications of Natural Language to Information Systems
Publisher :
Springer
Pages :
367-375
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Available on ORBilu :
since 24 June 2021

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