The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform
Magicarlo - One of the best experts on this subject based on the ideXlab platform.
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Properties of Line Spectrum pair polynomials
Signal Processing, 2006Co-Authors: Bäckströmtom, MagicarloAbstract:This review presents mathematical properties of Line Spectrum pair polynomials, especially those related to the location of their roots, a.k.a. Line spectral frequencies. The main results are three...
Hwang Soo Lee - One of the best experts on this subject based on the ideXlab platform.
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Interlacing properties of Line Spectrum pair frequencies
IEEE Transactions on Speech and Audio Processing, 1999Co-Authors: Hong Kook Kim, Hwang Soo LeeAbstract:An interlacing property of the Line Spectrum pair frequency (LSF) is proved on the basis of the logarithmic spectral difference function defined by the autoregressive models of successive orders. The property that the LSFs of an order are interlaced with those of lower order, provides a tight bound on the formant frequency region.
Carlo Magi - One of the best experts on this subject based on the ideXlab platform.
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Properties of Line Spectrum pair polynomials: a review
Signal Processing, 2006Co-Authors: Tom Bäckström, Carlo MagiAbstract:This review presents mathematical properties of Line Spectrum pair polynomials, especially those related to the location of their roots, a.k.a. Line spectral frequencies. The main results are three interlacing theorems for zeros on the unit circle, which we call the intra-model, inter-model and filtered-model interlacing theorems.
Stephanie S. Everett - One of the best experts on this subject based on the ideXlab platform.
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ICASSP - Word synthesis based on Line Spectrum pairs
ICASSP-88. International Conference on Acoustics Speech and Signal Processing, 1Co-Authors: Stephanie S. EverettAbstract:The author described the initial investigation of a synthetic speech system based on Line Spectrum pair (LSP) analysis of the speech signal. The synthesizer contains a library of stored LSP speech segments extracted from natural speech. These segments are modified as necessary by a small set of context-sensitive rules and then concatenated to generate high-quality natural-sounding speech. Tests of a preliminary system produced MRT and DRT scores of 87.3 and 79.7, respectively. The LSP vocabulary synthesizer is limited to utterances of a single syllable, but future research will expand its capabilities to allow implementation of a full text-to-speech system. >
Hou Tie-shuang - One of the best experts on this subject based on the ideXlab platform.
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Detection of Line Spectrum Signal Detection Based on Harmonic Wavelet Kernel-Support Vector Regression Algorithm
Computer Simulation, 2013Co-Authors: Hou Tie-shuangAbstract:To detection the weak signal under low SNR,based on the narrow-band signal analysis capability of the Harmonic Wavelet Function,and combined with the support vector regression,the Harmonic Wavelet Kernel Support Vector Regression algorithm was proposed for detecting the Line Spectrum signals under the condition of small samples.The simulation results with measured noise data show that the algorithm can detect the Line Spectrum signal in the Gaussian noise background effectively under the condition of small samples.