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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

Digital Audio Restoration

Simon Godsill

Signal Processing Group

University of Cambridge

www-sigproc.eng.cam.ac.uk/~sjg

overview
Overview
  • Audio Restoration - motivation
  • Audio Restoration in Cambridge 1984-2003
  • Review of core technologies
  • Audio restoration - principles
  • Advanced topics
  • Emerging techniques
audio restoration motivation
Audio Restoration - motivation
  • Requirement to enhance material from
    • Sound Archives:
    • Historical disk remastering:
    • `Recent’ Magnetic Tape recordings:
    • Forensic recordings, …
audio restoration in cambridge
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, …
core technologies
Core Technologies
  • De-click, de-crackle
  • De-hiss
  • Resonant noise pulse removal
de click de crackle
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
de hiss
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

resonant noise pulses
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
advanced topics
Advanced Topics
  • Bayesian statistical models
  • De-clipping/de-quantizing
  • Pitch variation defects (Wow)
resources
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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