In this research, several experiments were performed with sequential machine translation, using Google Translate tool. The experiments consisted of making sequential translations and, over 280 translations (using several available languages), evaluating the behavior of the translated text. In the academic article ‘An Empirical Accuracy Law for Sequential Machine Translation: the Case of Google Translate’, the authors found an unprecedented recurrence in the field: the fact that the accuracy of translation can be represented by a mathematical law. This law makes it possible to predict the behavior of translation chains, creating more efficient translation mechanisms for a world that is increasingly dependent on automated language devices.
Also from this investigation it is possible to understand that the logic of automatic translation is related to practices such as consumption, since most of the proper names become names of brands and products throughout the applied translation processes.
Participants: Lucas Nunes Sequeira, Bruno Moreschi, Fabio Gagliardi Cozman and Bernardo Fontes.