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Effects of real-time transcription on non-native speaker's comprehension in computer-mediated communications
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Conference on Human Factors in Computing Systems archive
Proceedings of the 27th international conference on Human factors in computing systems table of contents
Boston, MA, USA
SESSION: Computer mediated communication 2 table of contents
Pages 2353-2356  
Year of Publication: 2009
ISBN:978-1-60558-246-7
Authors
Yingxin Pan  IBM China Research Lab, Zhongguancun Software Park, Beijing, China
Danning Jiang  IBM China Research Lab, Zhongguancun Software Park, Beijing, China
Michael Picheny  IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
Yong Qin  IBM China Research Lab, Zhongguancun Software Park, Beijing, China
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

We performed an empirical study to understand the relative contributions of real-time transcription to a non-native speaker's comprehension in audio/video meetings. 48 participants were assigned to 2 presentation modes (audio, audio+video) and 3 transcription modes (no transcript, real-time transcripts in the streaming mode, transcripts with all past records) in a 3x2 factorial experimental design. The results suggest that comprehension can be significantly improved for both audio and audio+video conditions when real-time transcription is provided. Also, the participants reported positive subjective responses to the presence of real-time transcription in terms of usefulness, preference, and willingness to use such a feature if provided. No cognitive load issues were reported by the participants in the ability to synthesize across modalities. Implications for system development and design, as well as future work utilizing automation speech recognition to provide the transcripts are discussed.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Yingxin Pan: colleagues
Danning Jiang: colleagues
Michael Picheny: colleagues
Yong Qin: colleagues