Publication - Spectral Estimation for Speech Signals based on Decimation and Eigenanalysis
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Spectral Estimation for Speech Signals based on Decimation and Eigenanalysis

Research Area:  
    
Type:  
In Proceedings

 

Year: 2005
Authors: Pirros Tsiakoulis; Sotiris Karabetsos; Stavroula-Evita Fotinea; Ioannis Dologlou
Book title: Proc. HERCMA-2005 (7th Hellenic European Conf. on Computer Mathematics & its Applications)
Address: Athens, Greece
Date: Sept. 22-24
Abstract:
This paper details on the application of a Decimative Spectral estimation method to speech signals in order to perform spectral analysis and estimation of Formant/Bandwidth values. The method is based on Eigenanalysis and SVD (Singular Value Decomposition) and performs artificial decimation for increased accuracy while it exploits the full set of data samples. The underlying model decomposes a signal into complex damped sinusoids whose frequencies, amplitudes, phases and damping factors are estimated. Correct estimation of Formant/Bandwidth values depend on the model order, thus the requested number of poles. Additionally, some selection criteria are applied regarding finer tracking and estimation of speech formants and their relevant bandwidths.
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