International Conference on Computers for Handicapped Persons

ICCHP 2014: Computers Helping People with Special Needs pp 614-621 | Cite as

Performance Metrics and Their Extraction Methods for Audio Rendered Mathematics

  • Hernisa Kacorri
  • Paraskevi Riga
  • Georgios Kouroupetroglou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8547)


We introduce and compare three approaches to calculate structure- and content-based performance metrics for user-based evaluation of math audio rendering systems: Syntax Tree alignment, Baseline Structure Tree alignment, and MathML Tree Edit Distance. While the first two require “manual” tree transformation and alignment of the mathematical expressions, the third obtains the metrics without human intervention using the minimum edit distance algorithm on the corresponding MathML representations. Our metrics are demonstrated in a pilot user study evaluating the Greek audio rendering rules of MathPlayer with 7 participants and 39 stimuli. We observed that the obtained results for the metrics are significantly correlated between all three approaches.


Math Audio Rendering Metrics Accessibility MathML Usability 


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  1. 1.
    Freitas, D., Kouroupetroglou, G.: Speech Technologies for Blind and Low Vision Persons. Technology and Disability 20, 135–156 (2008)Google Scholar
  2. 2.
    Archambault, D., Stoger, B., Fitzpatrick, D., Miesenberger, K.: Access to scientific content by visually impaired people. UPGRADE VIII(2), 1–14 (2007)Google Scholar
  3. 3.
    Bates, E., Fitzpatrick, D.: Spoken mathematics using prosody, earcons and spearcons. In: Miesenberger, K., Klaus, J., Zagler, W., Karshmer, A. (eds.) ICCHP 2010, Part II. LNCS, vol. 6180, pp. 407–414. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Kouroupetroglou, G., Kacorri, H.: Deriving Accessible Science Books for the Blind Students of Physics. Proceedings of the American Institute of Physics 1203, 1308–1313 (2010)Google Scholar
  5. 5.
    Karshmer, A., Gupta, G., Pontelli, E., Miesenberger, K., Ammalai, N., Gopal, D., Batusic, M., Stöger, B., Palmer, B., Guo, H.: UMA: A System for Universal Mathematics Accessibility. In: Proceedings ASSETS 2004, the 6th Intern. ACM SIGACCESS Conference on Computers and Accessibility, Atlanta, Georgia, USA, October 18-20, vol. 196, p. 55. ACM (2004)Google Scholar
  6. 6.
    Tsonos, D., Kacorri, H., Kouroupetroglou, G.: A design-for-all approach towards multimodal accessibility of mathematics. Assistive Technology Research Series 25, 393–397 (2009)Google Scholar
  7. 7.
    Kacorri, H., Riga, P., Kouroupetroglou, G.: EAR-Math: Evaluation of Audio Rendered Mathematics. In: Stephanidis, C., Antona, M. (eds.) UAHCI 2014, Part II. LNCS, vol. 8514, pp. 111–120. Springer, Heidelberg (2014)Google Scholar
  8. 8.
    Soiffer, N.: A flexible design for accessible spoken math. In: Stephanidis, C. (ed.) UAHCI 2009, Part III. LNCS, vol. 5616, pp. 130–139. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  9. 9.
    Stevens, R.D.: Principles for the design of auditory interfaces to present complex information to blind people. Doctoral dissertation, University of York (1996)Google Scholar
  10. 10.
    Wongkia, W., Naruedomkul, K., Cercone, N.: I-Math: an Intelligent Accessible Mathematics system for People with Visual Impairment. Computational Approaches to Assistive Technologies for People with Disabilities 253, 83–108 (2013)Google Scholar
  11. 11.
    Fitzpatrick, D.: Towards Accessible Technical Documents: Production of Speech and Braille Output from Formatted Documents. Doctoral dissertation, Dublin City University (1999)Google Scholar
  12. 12.
    Murphy, E., Bates, E., Fitzpatrick, D.: Designing auditory cues to enhance spoken mathematics for visually impaired users. In: Proceedings of the 12th International ACM SIGACCESS Conference on Computers and Accessibility, pp. 75–82 (2010)Google Scholar
  13. 13.
    Zanibbi, R., Blostein, D., Cordy, J.R.: Baseline structure analysis of handwritten mathematics notation. In: Proc. of the 6th Int. Conf. Document Analysis and Recognition, pp. 768–773. IEEE (2001)Google Scholar
  14. 14.
    Zhang, K., Shasha, D.: Simple fast algorithms for the editing distance between trees and related problems. SIAM Journal on Computing 18(6), 1245–1262 (1989)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Pawlik, M., Augsten, N.: RTED: A Robust Algorithm for the Tree Edit Distance. PVLDB 5(4), 334–345 (2011)Google Scholar
  16. 16.
    Raman, T.V.: Mathematics for computer generated spoken documents–ASTeR Demonstration,
  17. 17.
    Acapela text-to-speech,

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Hernisa Kacorri
    • 1
    • 2
  • Paraskevi Riga
    • 1
  • Georgios Kouroupetroglou
    • 1
  1. 1.Department of Informatics and TelecommunicationsUniversity of AthensAthensGreece
  2. 2.Computer Science ProgramThe City University of New YorkNew YorkUSA

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