DocumentCode :
281579
Title :
Spectral estimation by damped sinusoidal modelling and singular value decomposition [speech recognition]
Author :
Farrier, D.R.
Author_Institution :
Dept. of Electr. Eng., Southampton Univ., UK
fYear :
1989
fDate :
32566
Firstpage :
42491
Lastpage :
42494
Abstract :
Looks at how to estimate spectra of decaying signals. It is interesting to note that there are again, two different methods. The first relies on forming a prediction filter (like LPC) and the second uses time-varying narrowband filters. Since the data is decaying, a LPC lattice structure is not appropriate, but signal-to-noise enhancement can be accomplished through the use of the singular value decomposition (SVD). The decaying signals lead to a need for unstable narrowband filters
Keywords :
filtering and prediction theory; spectral analysis; speech recognition; time-varying systems; LPC; damped sinusoidal modelling; decaying signals; prediction filter; signal-to-noise enhancement; singular value decomposition; spectral estimation; speech recognition; time-varying narrowband filters; unstable narrowband filters;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Spectral Estimation Techniques for Speech Processing, IEE Colloquium on
Conference_Location :
London
Type :
conf
Filename :
197938
Link To Document :
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