Logitboost weka classifier speech segmentation

Segmenting the speech signals on the basis of time-frequency analysis is the most natural approach. Boundaries are located in places where energy of some frequency subband rapidly changes. Speech segmentation method which bases on discrete wavelet transform, the resulting power spectrum and its derivatives is presented. This information allows to locate the boundaries of phonemes. A statistical classification method was used to check which features are useful. The efficiency of segmentation was verified on a male speaker taken from a corpus of Polish language.

• Type: Conference
• Year: 2008
• Where: ICMCS
• Authors: Bartosz Ziólko, Suresh Manandhar, Richard C. Wilson, Mariusz Ziólko
• Keywords: Discrete Wavelet Transform, ICMCS 2008, Multimedia, Speech Segmentation Method, Speech Signals