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Digital Audio Restoration Simon Godsill Signal Processing Group University of Cambridge www-sigproc.eng.cam.ac.uk/~sjg.

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Presentation on theme: "Digital Audio Restoration Simon Godsill Signal Processing Group University of Cambridge www-sigproc.eng.cam.ac.uk/~sjg."— Presentation transcript:

1 Digital Audio Restoration Simon Godsill Signal Processing Group University of Cambridge www-sigproc.eng.cam.ac.uk/~sjg

2 Overview n Audio Restoration - motivation n Audio Restoration in Cambridge 1984-2003 n Review of core technologies n Audio restoration - principles n Advanced topics n Emerging techniques

3 Audio Restoration - motivation n Requirement to enhance material from –Sound Archives: –Historical disk remastering: –`Recent’ Magnetic Tape recordings: –Forensic recordings, …

4 Audio Restoration in Cambridge n 1984-88 - British Library funds research into restoration of archived gramophone recordings at Signal Processing Group with Prof. Peter Rayner. n 1988 Cambridge company spun-out: CEDAR Audio. First real-time de- hiss and de-click in 1990, using DSP hardware on a PC platform. n 1990 -- Research into advanced audio processing at Cambridge University - Godsill, Rayner, Wolfe, Fong, …

5 Core Technologies n De-click, de-crackle n De-hiss n Resonant noise pulse removal

6 De-click/de-crackle

7 De-click/de-crackle n Time domain models for clicks and audio n Optimal detection and estimation of corrupted samples n Use fully Bayesian methods where time permits

8 De-hiss n Frequency-domain methods predominate n Non-linear processing of spectral information to incorporate local temporal and frequency dependence n Time-domain model-based methods also developed (joint click/hiss removal) * * Courtesy Patrick Wolfe – see www-sigproc.eng.cam.ac.uk/~pjw47 *

9 Resonant noise pulses n Tone-arm resonance in the presence of breakages or other severe damage to gramophone disk grooves n Simplest methods subtract an averaged template for the transient n More sophisticated methods apply a stochastic model for the resonant system

10 Low frequency noise pulse removal, contd.

11 Advanced Topics n Bayesian statistical models n De-clipping/de-quantizing n Pitch variation defects (Wow)

12 Future Directions

13 Resources n `Digital Audio Restoration - a statistical model-based approach’ by Simon Godsill and Peter Rayner, Springer- Verlag 1998 n See www-sigproc.eng.cam.ac.uk/~sjg for extracts, publications and sound examples


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