Cryptographic-speech-key generation using the SVM technique over the lp-cepstral speech space
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In this research we propose a new scheme for generating binary vectors, which can be used as keys for cryptographic purposes. These vectors are obtained from the speech signal and from the spoken user passphrase. The key bits are built using the Automatic Speech Recognition Technology to detect the phoneme limits in the speech utterance and the Support Vector Machines technique for classification. Linear prediction cepstral coefficients, (first and second derivatives) of the speech signal are calculated to create a 39-dimensional hyperspace. Then a hyperplane is created using an RBF kernel, and the SVM classifies the user's phonemes. Applying our method to a set of 10, 20, 30 and 50 speakers from the YOHO database, the results show that this method is sufficiently robust to reliably regenerate the cryptographic key. © Springer-Verlag Berlin Heidelberg 2005.