A reverse turing test using speech

Greg Kochanski, Daniel Lopresti, Chilin Shih

Research output: Contribution to conferencePaperpeer-review


"Hackers" have written malicious programs to exploit online services intended for human users. As a result, service providers need a method to tell whether a web site is being accessed by a human or a machine. We expect a parallel scenario as spoken language interfaces become common. In this paper, we describe a Reverse Turing Test (i.e., an algorithm that can distinguish between humans and computers) using speech. We present a test that depends on the fact that human recognition of distorted speech is far more robust than automatic speech recognition techniques. Our analysis of 18 different sets of distortions demonstrates that there are a variety of ways to make the problem hard for machines. In addition, humans and speech recognition systems make different kinds of mistakes, and this difference can be employed to improve discrimination.

Original languageEnglish (US)
Number of pages4
StatePublished - 2002
Externally publishedYes
Event7th International Conference on Spoken Language Processing, ICSLP 2002 - Denver, United States
Duration: Sep 16 2002Sep 20 2002


Other7th International Conference on Spoken Language Processing, ICSLP 2002
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language


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