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Full-Text Articles in Physical Sciences and Mathematics
Clustering Techniques In Speaker Recognition, Douglas N. Prescott
Clustering Techniques In Speaker Recognition, Douglas N. Prescott
Theses and Dissertations
This thesis presents a comparison based on identification rate, of three clustering techniques applied to cepstral features for speaker identification. LBG vector quantization as developed by Linde, Buzo and Gray; is used to provide benchmark performance for comparison with Fuzzy clustering (based on the unsupervised fuzzy partition-optimal number of classes, UFP-ONC algorithm by Gath and Geva) and an Artificial Neural Network, the Multilayer Perceptron. Cepstral features from the TIMIT, King and AFIT93 corpus speaker databases are used to produce speaker-identification classifiers using each of the clustering algorithms. The experiment reported evaluates the speaker identification performance using the 20-dimensional cepstral features …
Dyadic Wavelet Features For Isolated Word Speaker Dependent Speech Recognition, Stephen Ainge
Dyadic Wavelet Features For Isolated Word Speaker Dependent Speech Recognition, Stephen Ainge
Theses and Dissertations
This research examines the use of dyadic wavelet features for the recognition of speaker dependent isolated word speech. The features were generated using three different wavelet filters-Daubechies 4 coefficient (Db4), Daubechies 20 coefficient (Db20) and a 31 coefficient cubic spline and three different window lengths-15ms, 8ms and 4ms. The accuracy of the standard and over-sampled dyadic wavelet methods were compared. The over-sampled dyadic wavelet method using the Db4 scaling function, with a maximum accuracy of 65.5, was found to be the most accurate of the wavelet methods tested. The accuracy of this over-sampled dyadic Db4 wavelet method was compared to …