Date of Award
Thesis - Restricted
Master of Science (MS)
Electrical and Computer Engineering
Johnson, Michael T.
Povinelli, Richard J.
Struble, Craig A.
This research focuses on designing the SPEech Feature Toolbox (SPEFT), a toolbox which integrates a large number of speech features into one graphic interface in the MATLAB environment. The toolbox is designed with a Graphical User Interface (GUI) interface which makes it easy to operate; it also provides batch process capability. Available features are categorized into sub-groups including spectral features, pitch frequency detection, formant detection, pitch related features and other time domain features. A speaking style classification experiment is carried out to demonstrate the use of the SPEFT toolbox, and validate the usefulness of non-traditional features in classifying different speaking styles. The pitch-related features jitter and shimmer are combined with the traditional spectral and energy features MFCC and log energy. A Hidden Markov Models (HMMs) classifier is applied to these combined feature vectors, and the classification results between different feature combinations are compared. A thorough test of the SPEFT toolbox is also presented by comparing the extracted feature results between SPEFT and previous toolboxes across a validation test set.
Li, Xi, "SPEech Feature Toolbox (SPEFT) Design and Emotional Speech Feature Extraction" (2007). Master's Theses (1922-2009) Access restricted to Marquette Campus. 1315.