Architecture of Speech-based Registration System
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
Architecture of Speech-based Registration System

Authors: Mayank Kumar, D B Mahesh Kumar, Ashwin S Kumar, N K Srinath

Abstract:

In this era of technology, fueled by the pervasive usage of the internet, security is a prime concern. The number of new attacks by the so-called “bots", which are automated programs, is increasing at an alarming rate. They are most likely to attack online registration systems. Technology, called “CAPTCHA" (Completely Automated Public Turing test to tell Computers and Humans Apart) do exist, which can differentiate between automated programs and humans and prevent replay attacks. Traditionally CAPTCHA-s have been implemented with the challenge involved in recognizing textual images and reproducing the same. We propose an approach where the visual challenge has to be read out from which randomly selected keywords are used to verify the correctness of spoken text and in turn detect the presence of human. This is supplemented with a speaker recognition system which can identify the speaker also. Thus, this framework fulfills both the objectives – it can determine whether the user is a human or not and if it is a human, it can verify its identity.

Keywords: CAPTCHA, automatic speech recognition, keyword spotting.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1080780

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1551

References:


[1] Kumar Chellapilla, Kevin Larson, Patrice Simard, Mary Czerwinski (2005). "Computers beat Humans at Single Character Recognition in Reading based Human Interaction Proofs (HIPs)"
[2] Jeff Prosise (2001). "Programming Windows with MFC"
[3] Moni Naor (1996-09-13). "Verification of a human in the loop or Identification via the Turing Test"
[4] Rose, R.C.; Paul, D.B. "A hidden Markov model based keyword recognition system", ICASSP-90
[5] http://www.fcla.edu/digitalArchive/pdfs/ action_plan_ bgrounds/wav.pdf
[6] http://ccrma.stanford.edu/courses/422/projects/ Wave Format
[7] G. Saha, Sandipan Chakroborty, Suman Senapati, "A New Silence Removal and Endpoint Detection Algorithm forSpeech and Speaker Recognition Applications". Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Khragpur
[8] L.R.Rabiner and R.W.Schafer,"Digital Processing of Speech Signals", First Edition, Chapter 4, Pearson Education, Prentice-Hall.
[9] Christine Englund (2004), "Speech recognition in the JAS 39 aircraftadaptation at different G-loads", Master Thesis in Speech Technology
[10] Qiru Zhou and Wu chou, "An Approach to Continuous Speech Recognition Based on Layered Self-Adjusting Decoding Graph", Bell Laboratories, Lucent Technologies.