Fundamentals of speech recognition
Fundamentals of speech recognition
Machine Learning
Spoken Language Processing: A Guide to Theory, Algorithm, and System Development
Spoken Language Processing: A Guide to Theory, Algorithm, and System Development
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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This research shows the improvement obtained by including the principal component analysis as part of the feature production in the generation of a speech key. The main architecture includes an automatic segmentation of speech and a classifier. The first one, by using a forced alignment configuration, computes a set of primary features, obtains a phonetic acoustic model, and finds the beginnings and ends of the phones in each utterance. The primary features are then transformed according to both the phone model parameters and the phones segments per utterance. Before feeding these processed features to the classifier, the principal component analysis algorithm is applied to the data and a new set of secondary features is built. Then a support vector machine classifier generates an hyperplane that is capable to produce a phone key. Finally, by performing a phone spotting technique, the key is hardened. In this research the results for 10, 20 and 30 users are given using the YOHO database. 90% accuracy.