Abstract
In this research we propose to use phoneme spotting to improve the results in the generation of a cryptographic key. Phoneme spotting selects the phonemes with highest accuracy in the user classification task. The key bits are constructed by using the Automatic Speech Recognition and Support Vector Machines. Firstly, a speech recogniser detects the phoneme limits in each speech utterance. Afterwards, the support vector machine performs a user classification and generates a key. By selecting the highest accuracy phonemes for a a set of 10, 20, 30 and 50 speakers randomly chosen from the YOHO database, it is possible to generate reliable cryptographic keys.
Keywords
- Support Vector Machine
- Hide Markov Model
- Support Vector Machine Model
- Automatic Speech Recognition
- Speech Recogniser
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2005 Springer-Verlag Berlin Heidelberg
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García-Perera, L.P., Nolazco-Flores, J.A., Mex-Perera, C. (2005). Phoneme Spotting for Speech-Based Crypto-key Generation. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_80
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DOI: https://doi.org/10.1007/11578079_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
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