| Download | - View final version: Dialect and variant identification as a multi-label classification task: a proposal based on near-duplicate analysis (PDF, 319 KiB)
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| DOI | Resolve DOI: https://doi.org/10.18653/v1/2023.vardial-1.15 |
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| Author | Search for: Bernier-Colborne, Gabriel1; Search for: Goutte, Cyril1; Search for: Leger, Serge1 |
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| Affiliation | - National Research Council of Canada. Digital Technologies
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| Format | Text, Article |
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| Conference | Tenth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2023), May 5-6, 2023, Dubrovnik, Croatia |
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| Abstract | We argue that dialect identification should be treated as a multi-label classification problem rather than the single-class setting prevalent in existing collections and evaluations. In order to avoid extensive human re-labelling of the data, we propose an analysis of ambiguous near-duplicates in an existing collection covering four variants of French. We show how this analysis helps us provide multiple labels for a significant subset of the original data, therefore enriching the annotation with minimal human intervention. The resulting data can then be used to train dialect identifiers in a multi-label setting. Experimental results show that on the enriched dataset, the multi-label classifier produces similar accuracy to the single-label classifier on test cases that are unambiguous (single label), but it increases the macro-averaged F1- score by 0.225 absolute (71% relative gain) on ambiguous texts with multiple labels. On the original data, gains on the ambiguous test cases are smaller but still considerable (+0.077 absolute, 20% relative gain), and accuracy on nonambiguous test cases is again similar in this case. This supports our thesis that modelling dialect identification as a multi-label problem potentially has a positive impact. |
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| Publication date | 2023-05-05 |
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| Publisher | Association for Computational Linguistics |
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| Licence | |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | acc68ace-d317-45d0-bbea-243e601bbc0d |
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| Record created | 2023-05-15 |
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| Record modified | 2023-11-02 |
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