Jonathan Gabel Christiansen
2021
The Effect of Round-Trip Translation on Fairness in Sentiment Analysis
Jonathan Gabel Christiansen
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Mathias Gammelgaard
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Anders Søgaard
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Sentiment analysis systems have been shown to exhibit sensitivity to protected attributes. Round-trip translation, on the other hand, has been shown to normalize text. We explore the impact of round-trip translation on the demographic parity of sentiment classifiers and show how round-trip translation consistently improves classification fairness at test time (reducing up to 47% of between-group gaps). We also explore the idea of retraining sentiment classifiers on round-trip-translated data.
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