Puttick, Alexandre Riemann; Merhbene, Ghofrane; Kurpicz-Briki, Mascha (14 June 2023). To translate or not to translate? Exploring machine translation and multilingual models for mental health text classification In: SwissText 2023. Neuchâtel, Switzerland. 12 to 14 June 2023.
Full text not available from this repository. (Request a copy)It is often difficult to obtain a sufficient amount of training data for natural language processing methods when working with local languages. This challenge is even more present in the context of sensitive topics related to the detection of mental illnesses such as burnout. In this paper we explore the impact of machine translation and the use of multilingual models to mitigate this limitation. Specifically, we are interested in the potential for cross-lingual transfer learning, i.e., attempting to improve model performance by adding training data sourced from other languages. We compare different setups using monolingual BERT and multilingual BERT, applying different methods such as zero-shot transfer learning and joint training for a multilingual dataset consisting of English, German, French and Arabic examples. Our results suggest that low-resource languages may in some circumstances benefit from cross-lingual transfer learning.
Item Type: |
Conference or Workshop Item (Paper) |
|---|---|
Division/Institute: |
School of Engineering and Computer Science > Institute for Data Applications and Security (IDAS) School of Engineering and Computer Science > Institute for Data Applications and Security (IDAS) > IDAS / Applied Machine Intelligence School of Engineering and Computer Science |
Name: |
Puttick, Alexandre Riemann; Merhbene, Ghofrane and Kurpicz-Briki, Mascha |
Subjects: |
B Philosophy. Psychology. Religion > BF Psychology Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
Language: |
English |
Submitter: |
Mascha Kurpicz-Briki |
Date Deposited: |
09 Jan 2024 10:44 |
Last Modified: |
13 Mar 2024 10:18 |
URI: |
https://arbor.bfh.ch/id/eprint/20857 |
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