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Digital Audio Restoration

Digital Audio Restoration. Simon Godsill Signal Processing Group University of Cambridge www-sigproc.eng.cam.ac.uk/~sjg. Overview. Audio Restoration - motivation Audio Restoration in Cambridge 1984-2003 Review of core technologies Audio restoration - principles Advanced topics

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Digital Audio Restoration

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

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

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

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

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

  6. De-click/de-crackle

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

  8. De-hiss * * • Frequency-domain methods predominate • Non-linear processing of spectral information to incorporate local temporal and frequency dependence • 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 • Tone-arm resonance in the presence of breakages or other severe damage to gramophone disk grooves • Simplest methods subtract an averaged template for the transient • More sophisticated methods apply a stochastic model for the resonant system

  10. Low frequency noise pulse removal, contd.

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

  12. Future Directions

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

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