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Unformatted text preview: Speech Processing Analysis and Synthesis of PoleZero Speech Models February 13, 2012 Veton Këpuska 2 Introduction Deterministic: Speech Sounds with periodic or impulse sources Stochastic: Speech Sounds with noise sources Goal is to derive vocal tract model of each class of sound source. It will be shown that solution equations for the two classes are similar in structure. Solution approach is referred to as linear predication analysis . Linear prediction analysis leads to a method of speech synthesis based on the allpole model. Note that allpole model is intimately associated with the concatenated lossless tube model of previous chapter (i.e., Chapter 4). February 13, 2012 Veton Këpuska 3 AllPole Modeling of Deterministic Signals Consider a vocal tract transfer function during voiced source: … T=pitch U g [n] ⊗ A Glottal Model G( z ) Vocal Track Model V( z ) Radiation Model R( z ) s [n] Speech ( 29 ( 29 ( 29 ( 29 ( 29 ∑ == = P k k k z a A z H z R z V z AG z H 1 1 February 13, 2012 Veton Këpuska 4 AllPole Modeling of Deterministic Signals What about the fact that R(z) is a zero model? A single zero function can be expressed as a infinite set of poles. Note: From the above expression one can derive: ( 29 z a az az z a az k k k k k < ⇒ <= =∞ =∞ =∑ ∑ 1 , 1 1 1 1 1 ( 29 a z zb z a az k k k k k = =∏ ∑ ∞ =∞ =1 1 1 1 poles of number infinite 1 zero simple 1 February 13, 2012 Veton Këpuska 5 AllPole Modeling of Deterministic Signals In practice infinite number of poles are approximated with a finite site of poles since a k → 0 as k → ∞. H(z) can be considered allpole representation: representing a zero with large number of poles ⇒ inefficient Estimating zeros directly a more efficient approach (covered later in this chapter). February 13, 2012 Veton Këpuska 6 Model Estimation Goal  Estimate : filter coefficients {a 1 , a 2 , …,a p }; for a particular order p, and A, Over a short time span of speech signal (typically 20 ms) for which the signal is considered quasistationary. Use linear prediction method: Each speech sample is approximated as a linear combination of past speech samples ⇒ Set of analysis techniques for estimating parameters of the allpole model. February 13, 2012 Veton Këpuska 7 Model Estimation Consider ztransform of the vocal tract model: Which can be transformed into: In time domain it can be written as: Referred to us as a autoregressive (AR) model....
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 Fall '10
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 Regression Analysis, Signal Processing, Human voice, Phonation, Veton Këpuska, autocorrelation method

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