Abstract
Even though multilingual communities that use machine translation to overcome language barriers are increasing, we still lack a complete understanding of how machine translation affects communication. In this study, eight pairs from three different language communities - China, Korea, and Japan - worked on referential tasks in their shared second language (English) and in their native languages using a machine translation embedded chat system. Drawing upon prior research, we predicted differences in conversational efficiency and content, and in the shortening of referring expressions over trials. Quantitative results combined with interview data show that lexical entrainment was disrupted in machine translation-mediated communication because echoing is disrupted by asymmetries in machine translations. In addition, the process of shortening referring expressions is also disrupted because the translations do not translate the same terms consistently throughout the conversation. To support natural referring behavior in machine translation-mediated communication, we need to resolve asymmetries and inconsistencies caused by machine translations.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 20th Anniversary ACM Conference on Computer Supported Cooperative Work, CSCW 2006 |
| Pages | 515-524 |
| Number of pages | 10 |
| DOIs | |
| Publication status | Published - 2006 Dec 1 |
| Externally published | Yes |
| Event | 20th Anniversary ACM Conference on Computer Supported Cooperative Work, CSCW 2006 - Banff, AB, Canada Duration: 2006 Nov 4 → 2006 Nov 8 |
Publication series
| Name | Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW |
|---|
Conference
| Conference | 20th Anniversary ACM Conference on Computer Supported Cooperative Work, CSCW 2006 |
|---|---|
| Country | Canada |
| City | Banff, AB |
| Period | 06/11/4 → 06/11/8 |
Fingerprint
Keywords
- Computer-mediated communication
- Distributed work
- Lexical entrainment
- Machine translation
- Multilingual groups
- Reference
ASJC Scopus subject areas
- Software
- Human-Computer Interaction
- Computer Networks and Communications
Cite this
Effects of machine translation on collaborative work. / Yamashita, Naomi; Ishida, Toru.
Proceedings of the 20th Anniversary ACM Conference on Computer Supported Cooperative Work, CSCW 2006. 2006. p. 515-524 (Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Effects of machine translation on collaborative work
AU - Yamashita, Naomi
AU - Ishida, Toru
PY - 2006/12/1
Y1 - 2006/12/1
N2 - Even though multilingual communities that use machine translation to overcome language barriers are increasing, we still lack a complete understanding of how machine translation affects communication. In this study, eight pairs from three different language communities - China, Korea, and Japan - worked on referential tasks in their shared second language (English) and in their native languages using a machine translation embedded chat system. Drawing upon prior research, we predicted differences in conversational efficiency and content, and in the shortening of referring expressions over trials. Quantitative results combined with interview data show that lexical entrainment was disrupted in machine translation-mediated communication because echoing is disrupted by asymmetries in machine translations. In addition, the process of shortening referring expressions is also disrupted because the translations do not translate the same terms consistently throughout the conversation. To support natural referring behavior in machine translation-mediated communication, we need to resolve asymmetries and inconsistencies caused by machine translations.
AB - Even though multilingual communities that use machine translation to overcome language barriers are increasing, we still lack a complete understanding of how machine translation affects communication. In this study, eight pairs from three different language communities - China, Korea, and Japan - worked on referential tasks in their shared second language (English) and in their native languages using a machine translation embedded chat system. Drawing upon prior research, we predicted differences in conversational efficiency and content, and in the shortening of referring expressions over trials. Quantitative results combined with interview data show that lexical entrainment was disrupted in machine translation-mediated communication because echoing is disrupted by asymmetries in machine translations. In addition, the process of shortening referring expressions is also disrupted because the translations do not translate the same terms consistently throughout the conversation. To support natural referring behavior in machine translation-mediated communication, we need to resolve asymmetries and inconsistencies caused by machine translations.
KW - Computer-mediated communication
KW - Distributed work
KW - Lexical entrainment
KW - Machine translation
KW - Multilingual groups
KW - Reference
UR - http://www.scopus.com/inward/record.url?scp=34547145273&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34547145273&partnerID=8YFLogxK
U2 - 10.1145/1180875.1180955
DO - 10.1145/1180875.1180955
M3 - Conference contribution
SN - 1595932496
SN - 9781595932495
T3 - Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW
SP - 515
EP - 524
BT - Proceedings of the 20th Anniversary ACM Conference on Computer Supported Cooperative Work, CSCW 2006
ER -