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Investigating Viewer’s Reliance on Captions Based on Gaze Information

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12797))

Abstract

Subtitles are present in almost all TV programs and films in Taiwan. Are Taiwanese more dependent on subtitles to appreciate the content of the film compared to people of other nationality? What happens if subtitles are removed or replaced by unfamiliar languages? In this research, we use Tobii EyeX to collect eye movement data from 45 native-speakers while they watch different films, and propose appropriate indicators to analyze their viewing behavior. To facilitate subsequent data analysis, certain areas of interest (AOI), such as the caption region and human face, are automatically detected using techniques including Canny edge detector and Faster R-CNN.

Experimental results indicate that auditory language is the most critical factor. Subjects in Group #1 (English, Chinese, English and Chinese) have a higher tendency to focus on the face area. Subjects in Group #2 (Chinese, English, Chinese and English) appear to read the subtitles more often. The initial behavior seems to determine the viewing pattern subsequently. For subjects in Group #2, preference for caption is clearly observed than those in Group #1. This habitual preference continues in follow-up movies, resulting in an immersion phenomenon. We also observe that when unfamiliar texts appear, the subjects exhibit ‘escaping’ behavior by avoiding the text region. It is worth noting that the video at the beginning of Group #2 is the native language of the testee, and the result demonstrates that the subject develops preferences toward viewing subtitles. Therefore, we can partially confirm that Taiwanese people have a certain degree of dependence on subtitles.

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Correspondence to Wen-Hung Liao .

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Liao, WH., Chen, CJ., Wu, YC. (2021). Investigating Viewer’s Reliance on Captions Based on Gaze Information. In: Degen, H., Ntoa, S. (eds) Artificial Intelligence in HCI. HCII 2021. Lecture Notes in Computer Science(), vol 12797. Springer, Cham. https://doi.org/10.1007/978-3-030-77772-2_25

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  • DOI: https://doi.org/10.1007/978-3-030-77772-2_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77771-5

  • Online ISBN: 978-3-030-77772-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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