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Article In:
Approaches to Machine Translation
Edited by Mahdieh Fakhar, Monica Vilhelm and Paz Díez-Arcón
[Translation and Translanguaging in Multilingual Contexts 11:1] 2025
► pp. 48–64

Machine translation of tourism reviews

Quality assessment and localization

 | Universitat Politècnica de València
 | Universitat Politècnica de València
Machine translation (MT) has surpassed all quality expectations and its use has increased exponentially in recent years (Forcada 2017; Sánchez-Gijón, Moorkens, and Way 2019). One of the most frequent MT applications is the translation of user-generated content (UGC) and, more specifically, reviews on tourism portals such as Tripadvisor. Several authors agree that the degree of trust and credibility of a review, as the most important characteristics of UGC, depends largely on the perceived naturalness and authenticity of its writing (Pollach 2006; Schemmann 2011; Vásquez 2014). The review’s influence on the product’s reputation and on the purchase decision-making of future users has been fully demonstrated. Since review platforms make reviews available to users in different languages translated by MT, the quality of MT output should be studied from the point of view of the text’s adaptation to the requirements of a specific audience and market, following the principles elaborated in localization studies. The aim of this paper is to analyze the behavior of neural MT of user-generated content from the perspective of localization to check whether MT quality depends exclusively on linguistic or stylistic aspects or whether the aspects studied by localization, such as linguistic and cultural appropriateness for the target user, also play a decisive role. We compiled an English-Spanish parallel corpus consisting of 250 reviews retrieved from Tripadvisor. The reviews were originally written in English and MT processed into Spanish. Then the quality of the MT output was evaluated following two parameters: correctness and acceptance according to MT quality scales and localization guidelines.
Keywords: localization, machine translation, user generated content, quality
Article outline
  • 1.Introduction
  • 2.Importance and characteristics of UGC
  • 3.Current status of MT: Characteristics of neural machine translation
    • 3.1Quality parameters and metrics
    • 3.2Machine translation and localization
  • 4.Methodology
  • 5.Analysis and discussion
    • 5.1Evaluation of the MT quality of reviews
    • 5.2Localization problems
      • 5.2.1Localization errors: Cultural variants
      • 5.2.2Localization errors: Linguistic variant
    • 5.3Other causes affecting quality
      • 5.3.1Errors caused by explanations or duplications in the original text
      • 5.3.2Errors caused by typos in the original text
    • 5.4Summary of results
  • 6.Conclusions
  • References
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