UPA Perpustakaan Universitas Jember

Applications of speech-to-text recognition and computer-aided translation for facilitating cross-cultural learningthrough a learning activity: issues and their solutions

Rustam Shadiev1 - Personal Name
Ting-Ting Wu2 - Personal Name
Ai Sun3 - Personal Name
Yueh-Min Huang3 - Personal Name

In this study, 21 university students, who represented thirteen nationalities,participated in an online cross-cultural learning activity. The participants were engaged ininteractions and exchanges carried out on Facebook®and Skype®platforms, and theirmultilingual communications were supported by speech-to-text recognition (STR) andcomputer-aided translation (CAT) systems. The participants spoke in their native lan-guages, and the STR system generated texts from their voice input. The CAT system thensimultaneously translated the STR-texts into English. The aim of this study was to examinethe accuracy rates of STR and CAT processes for different languages during interculturalcommunication. We also explored issues associated with these processes and how theywere addressed in the study context. In addition, an attempt was made to determinewhether or not our learning activity as supported by STR and CAT technologies facilitatedcross-cultural learning. Our results showed that the lowest STR accuracy rate was forBelizean English whereas the highest STR accuracy rate was for French and Hindi. Thelowest CAT accuracy rate was for Mongolian and Filipino, and the highest was forSpanish, Russian, and French. Seven issues associated with the STR process and ten issuesassociated with the CAT process were identified. The participants employed ten work-arounds 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 overcomea limitation related to either STR or CAT. Finally, our results demonstrated that cross-cultural learning took place; the participants understood and could explain foreign tradi-tions to others and could also compare foreign traditions with their own. Based on ourresults, we made several suggestions and provided implications for the teaching andresearch community.

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Speech-to-text recognition
Computer-aided translation
Cross-culturallearning
Accuracy rate
Issues
Workarounds

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Applications of speech-to-text recognition and computer-aided translation for facilitating cross-cultural learning through a learning activity: issues and their solutions

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NPP. 3509212D1000001

Applications of speech-to-text recognition and computer-aided translation for facilitating cross-cultural learningthrough a learning activity: issues and their solutions

Rustam Shadiev1 - Personal NameTing-Ting Wu2 - Personal NameAi Sun3 - Personal NameYueh-Min Huang3 - Personal Name

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Rustam Shadiev1 - Personal Name
Ting-Ting Wu2 - Personal Name
Ai Sun3 - Personal Name
Yueh-Min Huang3 - Personal Name