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Applying speech-to-text recognition and computer-aided translation for supporting multi-lingual communications in cross-cultural learning project
Rustam Shadiev1; Barry Lee Reynolds2; Yueh-Min Huang3; Narzikul Shadiev4; Wei Wang1; Rai Laxmisha5; Wanwisa Wannapipat6
2017
Conference Name2017 IEEE 17TH INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES (ICALT)
Source Publication2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT)
Pages182-183
Conference Date3-7 July 2017
Conference PlaceTimisoara, Romania
CountryRomania
Publication Place345 E 47TH ST, NEW YORK, NY 10017 USA
PublisherIEEE
Abstract

We applied a speech-to-text recognition (STR) and computer-aided translation (CAT) systems to support multilingual communications students participating in cross-cultural learning project. The participants were engaged in interactions and information exchanges in order to learn and understand cultures and traditions of their peers. Their communications were carried out in their native languages on social communication platforms. The participants spoke and STR system generated texts from their voice inputs. CAT system then simultaneously translated STR-texts into English. Finally, translated texts were posted on social communication platforms along with spoken content in the participants' native languages. We aimed to examine accuracy rates of processes associated with STR and CAT for different languages during multi-lingual communications in our cross-cultural learning project. In addition, the feasibility of our approach to support multi-lingual communications in cross-cultural learning project was investigated. Our results showed that the lowest accuracy rate was for Mongolian and Filipino and the highest was for Spanish, Russian, and French. Our results also demonstrated that cross-cultural learning took place; the participants understood and were able to explain foreign traditions to others as well as to compare foreign traditions with their own local. Based on our results, we made several suggestions and implications for the teaching and research community.

KeywordSpeech-to-text Recognition Computer-aided Translation Cross-cultural Learning Accuracy Rate
DOI10.1109/ICALT.2017.20
URLView the original
Indexed ByISSHP ; CPCI
Language英語English
WOS Research AreaComputer Science ; Education & Educational Research
WOS SubjectComputer Science, Information Systems ; Computer Science, Interdisciplinary Applications ; Education & Educational Research
WOS IDWOS:000427129000054
The Source to ArticleWOS
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Document TypeConference paper
CollectionFaculty of Education
Affiliation1.Nanjing Normal University, Nanjing, China
2.University of Macau, Macau, China
3.National Cheng Kung University, Tainan, Taiwan
4.Samarkand State University, Samarkand, Uzbekistan
5.Shandong University of Science and Technology, Qingdao, China
6.Khon Kaen University, Khon Kaen, Thailand
Recommended Citation
GB/T 7714
Rustam Shadiev,Barry Lee Reynolds,Yueh-Min Huang,et al. Applying speech-to-text recognition and computer-aided translation for supporting multi-lingual communications in cross-cultural learning project[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2017:182-183.
APA Rustam Shadiev,Barry Lee Reynolds,Yueh-Min Huang,Narzikul Shadiev,Wei Wang,Rai Laxmisha,&Wanwisa Wannapipat.(2017).Applying speech-to-text recognition and computer-aided translation for supporting multi-lingual communications in cross-cultural learning project.2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT),182-183.
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