Abstract
Eye movements made when reading text are considered to be important clues for estimating both understanding and interest. To analyze gaze data captured by the eye tracker with respect to a text, we need a noise-robust mapping between a fixation point and a word in the text. In this paper, we propose a dynamic-programming–based method for effective fixation-to-word mappings that can reduce the vertical displacement in gaze location. The golden dataset is created using FixFix, our web-based manual annotation tool. We first divide the gaze data into a number of sequential reading segments, then attempt to find the best segment-to-line alignment. To determine the best alignment, we select candidates for each segment, and calculate the cost based on the length characteristics of both the segment and document lines. We compare our method with the naïve mapping method, and show that it is capable of producing more accurate fixation-to-word mappings.
This work was supported by JSPS KAKENHI Grant Number 24300062.
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Hornof, A., Halverson, T.: Cleaning up systematic error in eye-tracking data by using required fixation locations. Behav. Res. Methods 34, 592–604 (2002)
Hyrskykari, A.: Utilizing eye movements: overcoming inaccuracy while tracking the focus of attention during reading. Comput. Hum. Behav. 22, 657–671 (2005)
Abhijit, M., Michael, C., Pushpin, B.: A heuristic-based approach for systematic error correction of gaze data for reading. In: 24th International Conference on Computational Linguistics, pp. 71–80 (2012)
Michael, C.: Dynamic programming for re-mapping noisy fixations in translation tasks. J. Eye Mov. Res. 6(2), 1–11 (2013)
Pascual, M.G., Akiko, A.: Recognition of understanding level and language skill using measurements of reading behavior. In: 2014 International Conference on Intelligent User Interfaces (IUI-2014), pp. 95–104 (2014)
Salvucci, D.D., Joseph, H.G.: Identifying fixations and saccades in eye-tracking protocols. In: Proceedings of the 2000 Symposium on Eye Tracking Research & Applications. ACM (2000)
Holmqvist, K., et al.: Eye tracking: a comprehensive guide to methods and measures. Oxford University Press (2011)
Ralf, B., Jörn, H., Andreas, D., Georg, B.: A robust realtime reading-skimming classifier. In: The Symposium on Eye Tracking Research and Applications (ETRA’12), pp. 123–130 (2012)
Ryohei, T., Tadayoshi, H., Akiko, A.: Text width optimization based on gaze information. In: The 27th Annual Conference of the Japanese Society for Artificial Intelligence (2013) (in Japanese)
Needleman, S.B., Christian, D.W.: A general method applicable to the search for similarities in the amino acid sequence of two proteins. J. Mol. Biol. 443–453 (1970)
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Yamaya, A., Topić, G., Martínez-Gómez, P., Aizawa, A. (2015). Dynamic-Programming–Based Method for Fixation-to-Word Mapping. In: Neves-Silva, R., Jain, L., Howlett, R. (eds) Intelligent Decision Technologies. IDT 2017. Smart Innovation, Systems and Technologies, vol 39. Springer, Cham. https://doi.org/10.1007/978-3-319-19857-6_55
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DOI: https://doi.org/10.1007/978-3-319-19857-6_55
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