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Audio Captcha Recognition Using RastaPLP Features by SVM
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Nowadays, CAPTCHAs are computer generated tests that human can pass but current computer systems can not. They have common usage in various web services in order to be able to detect a human from computer programs autonomously. In this way, owners can protect their web services from bots. In addition to visual CAPTCHAs which consist of distorted images, mostly test images, that a user must write some description about that image, there are a significant amount of audio CAPTCHAs as well. Briefly, audio CAPTCHAs are sound files which consist of human sound under heavy noise where the speaker pronounces a bunch of digits consecutively. Generally, in those sound files, there are some periodic and non-periodic noises to get difficult to recognize them with a program but not for a human listener. We gathered numerous randomly collected audio file to train and then test them using our SVM algorithm to be able to extract digits out of each conversation.
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Cited by 1 Pith paper
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Moravec's Paradox: Towards an Auditory Turing Test
The paper proposes an auditory Turing test of 917 challenges and reports that the best tested AI model, GPT-4o audio, scores 6.9% versus 52% for a nine-person human sample.
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