An analysis of expert knowledge transmission using machine translation services

Abstract

Due to globalization, there is an increase in not only the use of machine translation services but also in the risk of failure to transfer. This risk becomes particularly significant if users are transmitting their country's specific knowledge and know-how to exchange cultural information with users in other countries. To mitigate this risk, it is necessary for users to adapt to the translation services in order to improve the translation's accuracy. Thus, in this study we focused on the transmission effect of sharing technical knowledge with a user having a different mother tongue (Chinese) by using a machine translation service. We performed experiments simulating expert knowledge transmission classes and tasks with a system consisting of multilingual chats and a corpus of terminologies. Our evaluation of the transmission reveals how the Chinese knowledge receiver could have learned depending on the pattern of organizational structure and the level of detail of the information. We also found that the use of symbols and numbers was effective. After these simulations and evaluation, we were able to propose how to more effectively use machine translation in the transmission of technical knowledge.