A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Wordspotting for voice editing and audio indexing
CHI '92 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fundamentals of speech recognition
Fundamentals of speech recognition
Machine Learning
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Cryptographic Key Generation from Voice
SP '01 Proceedings of the 2001 IEEE Symposium on Security and Privacy
Support Vector Machines: Training and Applications
Support Vector Machines: Training and Applications
Features and measures for speaker recognition
Features and measures for speaker recognition
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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.