the cups blog


SOAPS: Towards a Universally Usable CAPTCHA

Graig Sauer, Harry Hochheiser, Hedi Feng and Jonathan Lazar


  • Types: Character, Image, Anomaly, Recognition, Sound
  • Examples: Gimpy, EZGIMPY, reCAPTCHA

Accessibility Concerns

  • Initially, CAPTCHAs were visual, then added audio to encompass more accessibility options

Study of accessibility/usability of audio reCAPTCHA

  • Potential concerns:
    • User comprehension, cognitive load, interference with screen readers (ie, overlapping sound with the CAPTCHA), frustrations as a result of the CAPTCHA
  • Design:
    • Jaws, external aids: braille note taker, MS Word
    • test: six attempts (one practice), short demographics survey
  • Demographics (averages, n=6): 14.5 year computer use, 7.25 hours of daily use, 7 out of 10 Jaws experience.
  • Results: avg 2.33 attempts correct, 46%
    • 90% correctness is acceptable (from Chellapilla et al.), much above what was observed
    • Schuluessler et al. suggests 51s is an acceptable completion time, this study showed 65.54s for correct, 59.56 from failed attempts.
    • Participants using external aids had higher performance on the task.

Question: What is a good measure for “good enough” (vs. the reported 5% beatable that’s taken as the worst)

  • Are these situational/threat model related questions?

Participant complaints: audio clarity, having to guess answers

Towards an Accessible CAPTCHA:

  • Universal Usability: Products and services that are usable for every citizen. Separation between systems.
  • Human Interaction Proof, Universally Usable (HIPUU)
    • Visual and Audio HIP
    • Challenges: search space, file recognition (checksums, signatures), input type
    • expanded prototype: sound merging, drop down list, free text input
    • Universal Usability: both visual and audio systems deployed concurrently
    • Further development options: expansion of the search space, free text vs. drop down list, in-audible white noise (to confound checksums and file length comparisons)
    • Planned studies: usability of the expanded HIPUU, free-text study, online user study

Q: Are there enough sound options to defeat machine training?

A: White-noise insertion, for instance, could be hard to insert without still being possible for automatic removal.