By Bernd Iser
Bandwidth Extension of Speech signs presents dialogue on diverse methods for effective and strong bandwidth extension of speech indications whereas acknowledging the impression of noise corrupted real-world signs. The ebook describes the idea and strategies for caliber enhancement of fresh speech indications and distorted speech signs reminiscent of those who have passed through a band difficulty, for example, in a cellphone community. difficulties and the respective suggestions are mentioned with regard to diversified ways. different methods are evaluated and robustness matters for a real-time implementation are coated to boot. The ebook contains subject matters relating to speech coding, trend- / speech reputation, speech enhancement, information and electronic sign processing in general.
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Rss,n (P − 1) ⎢ a2 . . rss,n (P − 2) ⎥ ⎥⎢ ⎥ ⎢ .. ⎦⎣ . aP rss,n (P − 1) rss,n (P − 2) . . rss,n (0) Rss,n a ⎤ ⎥ ⎥ ⎥ . 1 Linear Predictive Analysis 23 Solving this equation for the optimal predictor coeﬃcients ai leads to a = R−1 ss,n rss,n . 30) This equation is only solvable for Rss,n being positive deﬁnite and therefore invertible. Since the matrix Rss,n is symmetric and has Toeplitz structure, there exist very eﬃcient algorithms to solve this set of equations [Rabiner 93]. The most popular one, the so-called Levinson–Durbin recursion, is presented in Appendix A.
This is due to the fact that some of the algorithms for extending the excitation signal presented in this book perform a spectral coloration which has to be reversed. In this chapter we also describe how to adjust the power of the estimated broadband excitation signal to the 54 4 Excitation Signal Extension anb(n) snb(n) Whitening filter enb(n) Excitation signal extension Power adjustment Whitening filter eˆbb(n) Fig. 1. Overall system for excitation signal extension Spectrum of snb(n) Spectrum of enb(n) 20 snb(n) 0 enb(n) −20 z−1 −40 −60 ai,nb(n) Magnitude [dB] Magnitude [dB] 20 0 −20 −40 −60 0 1000 2000 3000 4000 5000 Frequency [Hz] 0 1000 2000 3000 4000 5000 Frequency [Hz] Fig.
36) for each tube segment with a constant cross-sectional area Ai to v=− ∂ 2 Φi 1 ∂ 2 Φi = 2 . 2 Parametric Representations of the Spectral Envelope A1 A2 A3 A4 1 2 3 4 25 x Lips Glottis Fig. 3. 40) exist. Here Φ+ i denotes the wave that propagates in positive x-direction (forward) of segment i, whereas Φ− i denotes the wave that propagates in negative x-direction (backward) within the tube segment i, where x is measured from the glottal end of each tube (0 ≤ x ≤ i ). 38) we can formulate the sound particle velocity as vi (x, t) = x x 1 + t+ Φi t − − Φ− i c c c .
Bandwidth Extension of Speech Signals by Bernd Iser