Machine Translation in Tourism: Implications for the Hospitality Industry

Resumo

Objetivos | Accelerated globalization and advancements in mobility have implied an increased contact between different linguistic tourism markets. Despite the centrality of language in the tourism phenomenon, this relationship has scarcely been analyzed in tourism literature. However, communication across different languages is essential for successful intercultural communication, negotiation, and persuasion in the context of international tourism. However, despite the importance of language skills, the increasing globalization of the tourism industry makes it unlikely that an individual acquires sufficient knowledge in all the languages that they might encounter either as a host or as a guest. In addition, human translators are not at hand in all situations, and they imply costs. Hence, machine translation (MT), i.e., automatic translation, may be a viable alternative in many situations. In the past few years, advancements in artificial intelligence (AI) have led to a rampant evolution in the field of human translation – e.g., the Google Translate app alone had been downloaded one billion times by March 2021. However, despite the impact of this technology on society, businesses and individuals, the implications of these developments for how individuals communicate across languages have been scarcely analyzed by previous literature, and the use of MT in the tourism sector remains as a huge research gap to be filled.

The present study aims to analyze the use of MT tools in the hospitality industry. It answers the following research question: What are the implications of MT use in the hospitality industry? The specific research objectives of this study are: i) to investigate perceptions and satisfaction with MT use among hotel employees and managers; ii) to analyze how MT technology is used by hotel employees (i.e., name of MT tools used, types of circumstances, purposes, frequency of use, used languages, use of text vs. speech translation etc.); iii) to ascertain potential risks and limitations of MT use; iv) to determine the relevance of improving MT literacy among hotel employees and managers, and strategies for improving such literacy; and v) to find out technological improvements desired by different types of hospitality businesses.

Metodologia | This study adopted a qualitative approach. Firstly, we carried out semi-structured in-depth interviews with experts in several fields, including both academic and business experts (e.g., translation, computational linguistics, machine translation, artificial intelligence, and tourism). Secondly, we carried out interviews 30 with hotel employees and hotel directors in Barcelona and Lisbon. Content analysis was carried out with the assistance of the software MaxQDA.

Principais resultados e contributos | The main contributions of this study are: i) a better understanding of how MT technologies can benefit the hospitality industry, considering both businesses and tourists; ii) promoting MT literacy and an appropriate use of MT tools, considering its risks, limitations and drawbacks; iii) and providing directions for how MT technology could further develop to satisfy businesses and employees’ desires and needs. Theoretically, we contribute to the scarce literature on technology-mediated communication in the tourism context.

Limitações | This study had a qualitative nature. Therefore, results cannot be generalized to other contexts.

Conclusões | The increasing reliance on machine translation (MT) in the globalized tourism sector necessitates an understanding of its implications in the hospitality industry. This research underscores the potential of MT as a valuable tool, facilitating communication across diverse linguistic barriers. While MT promises increased efficiency and reduced costs, it is essential for hospitality professionals to be literate in its use, and cognizant of its limitations. Despite the importance that the interviewees assigned to MT, the majority did not consider that it presently replaces the need for employees to acquire language skills. As language technology (e.g., ChatGPT) continues to advance, ongoing research is essential to track the evolving implications addressed in this study

Referências bibliográficas

Stewart, D. (2019). English for tourism in the non-native English classroom: Machine translation and corpora. In: M.J. Ennis & G.M. Petrie (Eds.), Teaching English for Tourism: Bridging Research and Praxis (pp. 114-130). Routledge. DOI: 10.4324/9780429032141

Vieira, L. N., O’Sullivan, C., Zhang, X., & O’Hagan, M. (2022). Machine translation in society: insights from UK users. Language Resources and Evaluation. https://doi.org/10.1007/s10579-022-09589-1

Yamada, M. (2019). Language learners and non-professional translators as users. In M. O’Hagan (Ed.) The Routledge handbook of translation and technology (pp. 183-199). Routledge. DOI: 10.4324/9781315311258-11