Measuring Sentiment Bias in Machine Translation

• URL: http://arxiv.org/abs/2306.07152v1
• Date: Mon, 12 Jun 2023 14:40:29 GMT
• Title: Measuring Sentiment Bias in Machine Translation
• Authors: Kai Hartung, Aaricia Herygers, Shubham Kurlekar, Khabbab Zakaria, Taylan Volkan, S\"oren Gr\"ottrup, Munir Georges
• Abstract summary: Biases induced to text by generative models have become an increasingly large topic in recent years. We compare three open access machine translation models for five different languages on two parallel corpora. Though our statistic test indicate shifts in the label probability distributions, we find none that appears consistent enough to assume a bias induced by the translation process.
• Score: 1.567333808864147
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Biases induced to text by generative models have become an increasingly large topic in recent years. In this paper we explore how machine translation might introduce a bias in sentiments as classified by sentiment analysis models. For this, we compare three open access machine translation models for five different languages on two parallel corpora to test if the translation process causes a shift in sentiment classes recognized in the texts. Though our statistic test indicate shifts in the label probability distributions, we find none that appears consistent enough to assume a bias induced by the translation process.

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