Ertan, Ali Erdem2016-01-082016-01-081998http://hdl.handle.net/11693/18071Ankara : Department of Electrical and Electronics Engineering and The Institute of Engineering and Sciences of Bilkent University, 1998.Thesis (Master's) -- Bilkent University, 1998.Includes bibliographical references leaves 124-132In this thesis, two new speech variation measures for speech spectrum nonstationarity detection are proposed. These measures are based on the Line Spectrum Frequencies (LSF) and the spectral values at the LSF locations. They are formulated to be subjectively meaningful, mathematically tractable, and also have low computational complexity property. In order to demonstrate the usefulness of the non-stationarity detector, two applications are presented: The first application is an implicit speech segmentation system which detects non-stationary regions in speech signal and obtains the boundaries of the speech segments. The other application is a Variable Bit-Rate Mixed Excitation Linear Predictive (VBR-MELP) vocoder utilizing a novel voice activity detector to detect silent regions in the speech. This voice activity detector is designed to be robust to non-stationary background noise and provides efficient coding of silent sections and unvoiced utterances to decrease the bit-rate. Simulation results are also presented.xvi, 132 leavesEnglishinfo:eu-repo/semantics/openAccessSpeech variation measure,Spectrum non-stationarity detectionFormant estimationLine Spectrum Frequencies (LSF)Speech segmentationMixed Excitation Linear Predictive coding (MELP)Variable bit-rate vocoderVoice activity detectorTK7882.S65 E78 1998Speech processing systems.Vocoder.Thesis