Spectral Processing

DAFX: Digital Audio Effects: Second Edition

Volumn , Issue , 2011, Pages 393-445

  Bonada, J ^a   Serra, X ^a   Amatriain, X ^a,b   Loscos, A ^c  

^a UNIVERSITAT POMPEU FABRA   (Spain)

^b TELEFONICA RESEARCH   (Spain)

^c Universitat Pompeu Fabra ^*

Author keywords

MATLAB code and morphing algorithm interpolation of harmonic and residual components of two sounds; Pitch transposition, scaling of partials of sound same multiplying factor; Representations of sound signals and signal processing systems design sound transformations for musical applications; Spectral harmonics plus stochastic residual; Spectral harmonics, constraints in sinusoidal model, restricting sinusoids into being harmonic partials; Spectral model approach time domain signal conversion to its frequency domain representation, the short time fourier transform (STFT); Spectral models based on STFT sound and music signals, fulfilling compromises and applications; Spectral processing; Spectral processing, analyzing a sound obtaining alternative frequency domain representations; Spectral representation of sound close to one used in sound engineering approaches

Indexed keywords

EID: 84886053393     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9781119991298.ch10     Document Type: Chapter

References (29)

1. J. Bonada. Wide-band harmonic sinusoidal modeling. In Proc. 11th Int. Conf. Digital Audio Effects (DAFx-08), 2008.
2. P. Cano. Fundamental frequency estimation in the SMS analysis. In Proc. DAFX-98 Digital Audio Effects Workshop, pp. 99-102, 1998.
3. D. G. Childers. Measuring and modeling vocal source-tract interaction. IEEE Trans. Biomed. Eng., 41(7): 663-671, 1994.
4. A. Cheveigné and H. Kawahara. YIN, A fundamental frequency estimator for speech and music. J. Acoust. Soc. Am., 111(4): 1917-1930, 2002.
5. M. G. Cox. An algorithm for approximating convex functions by means of first-degree splines. Comp. J ., 14: 272-275, 1971.
6. Ph. Depalle, G. Garcia and X. Rodet. Analysis of sound for additive synthesis: tracking of partials using Hidden Markov models. In Proc. Int. Comp. Music Conf ., pp. 94-97, 1993.
7. Ph. Depalle and T. Hélie. Extraction of spectral peak parameters using a short-time Fourier transform modeling and no sidelobe windows. In Proc. 1997 IEEE Workshop Appl. Signal Process. Audio Acoust ., pp. 298-231, 1997.
8. R. DiFederico. Waveform preserving time stretching and pitch shifting for sinusoidal models of sound. In Proc. DAFX-98 Digital Audio Effects Workshop, 1998.
9. Y. Ding and X. Qian. Sinusoidal and residual decomposition and residual modeling of musical tones using the QUASAR signal model. In Proc. Int. Comp. Music Conf ., pp. 35-42, 1997.
10. K. Fitz, L. Haken, and P. Christensen. A new algorithm for bandwidth association in bandwidthenhanced additive sound modeling. In Proc. Int. Com. Music Conf ., pp. 384-387, 2000.
11. M. Goodwin. Adaptative signal models: Theory, algorithms and audio applications. PhD thesis, University of California, Berkeley, 1997.
12. W. Hess. Pitch Determination of Speech Signals. Springer-Verlag, 1983.
13. J. Laroche. Frequency-domain techniques for high-quality voice modification. In Proc. 6th Int. Conf Digital Audio Effects (DAFx-03), 2003.
14. J. Makhoul. Linear prediction: a tutorial review. Proce IEEE, 63(4): 561-580, 1975.
15. R. C. Maher and J. W. Beauchamp. Fundamental frequency estimation of musical signals using a two-way mismatch procedure. J. Acoust. Soc. Am., 95(4): 2254-2263, 1994.
16. S. Musevic and J. Bonada. Comparison of non-stationary sinusoid estimation methods using reassignment and derivatives. In Proc. Sound Music Computing Conf 2010.
17. J. D. Markel and A. H. Gray. Linear Prediction of Speech. Springer-Verlag, 1975.
18. R. J. McAulay and T. F. Quatieri. Speech analysis/synthesis based on a sinusoidal representation. IEEE Trans Acoustics Speech Signal Process, 34(4): 744-754, 1986.
19. G. Peeters. Modéles et modification du signal sonore adaptàsá ses caractéristiques locales. PhD thesis, spécialité Acoustique Traitement du signal et Informatique Appliquès á la Musique, Universite Paris 6, 2001.
20. X. Rodet and Ph. Depalle. Spectral envelopes and inverse FFT synthesis. Proc. 93rd AES Conve. AES Preprint No. 3393 (H-3), 1992.
21. R. Sedgewick. Algorithms. Addison-Wesley, 1988.
22. X. Serra. A System for Sound Analysis/Transformation/Synthesis based on a Deterministic plus Stochastic Decomposition. PhD thesis, Stanford University, 1989.
23. X. Serra. Musical sound modeling with sinusoids plus noise. In G. De Poli, A. Picialli, S. T. Pope, and C. Roads (eds), Musical Signal Processing, pp. 91-122, Swets & Zeitlinger Publishers, 1996.
24. J. O. Smith and X. Serra. PARSHL: an analysis/synthesis program for non-harmonic sounds based on a sinusoidal representation. In Proc. Int. Comp. Music Conf ., pp. 290-297, 1987.
25. X. Serra and J. Smith. Spectral modeling synthesis: a sound analysis/synthesis system based on a deterministic plus stochastic decomposition. Comp. Music J ., 14(4): 12-24, 1990.
26. J. Strawn. Approximation and syntactic analysis of amplitude and frequency functions for digital sound synthesis. Comp. Music J ., 4(3): 3-24, 1980.
27. T. S. Verma and T. H. Y. Meng. Time scale modification using a sines+transients+noise signal model. In Proc. DAFX-98 Digital Audio Effects Workshop, pp. 49-52, 1998.
28. T. S. Verma and T. H. Y. Meng. Extending spectral modeling synthesis with transient modeling synthesis. Comp. Music J ., 24(2): 47-59, 2000.
29. M. Zivanovic, A. Röbel and X. Rodet. Adaptive threshold determination for spectral peak classification. In Proc. 10th Int. Conf. Digital Audio Effects (DAFx-07), 2007.