In this study, 21 university students, who represented thirteen nationalities, participated in an online cross-cultural learning activity. The participants were engaged in interactions and exchanges carried out on Facebook® and Skype® platforms, and their multilingual communications were supported by speech-to-text recognition (STR) and computer-aided translation (CAT) systems. The participants spoke in their native languages, and the STR system generated texts from their voice input. The CAT system then simultaneously translated the STR-texts into English. The aim of this study was to examine the accuracy rates of STR and CAT processes for different languages during intercultural communication. We also explored issues associated with these processes and how they were addressed in the study context. In addition, an attempt was made to determine whether or not our learning activity as supported by STR and CAT technologies facilitated cross-cultural learning. Our results showed that the lowest STR accuracy rate was for Belizean English whereas the highest STR accuracy rate was for French and Hindi. The lowest CAT accuracy rate was for Mongolian and Filipino, and the highest was for Spanish, Russian, and French. Seven issues associated with the STR process and ten issues associated with the CAT process were identified. The participants employed ten workarounds to address the STR-related issues and thirteen workarounds to address the CAT-related issues. We refer to a workaround as a method used by the participants to overcome a limitation related to either STR or CAT. Finally, our results demonstrated that cross-cultural learning took place; the participants understood and could explain foreign traditions to others and could also compare foreign traditions with their own. Based on our results, we made several suggestions and provided implications for the teaching and research community.
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