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User-Driven Quality Enhancement for Audio Signal Processing

134th AES CONVENTION Rome, Italy – 2013 May 4-7. Convention Paper 8823. User-Driven Quality Enhancement for Audio Signal Processing. D. Comminiello , S. Scardapane, M. Scarpiniti, A. Uncini. 2013 May 4-7. Outline of the Talk. (1). Problem Definition Our Framework. (2).

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User-Driven Quality Enhancement for Audio Signal Processing

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  1. 134th AES CONVENTION Rome, Italy – 2013 May 4-7 Convention Paper8823 User-Driven Quality Enhancement for Audio Signal Processing D. Comminiello, S. Scardapane, M. Scarpiniti, A. Uncini

  2. 2013 May 4-7 Outline of the Talk • (1) • Problem Definition • Our Framework • (2) • Applications • Immersive Speech, Games… • (3) • Preliminary Results • Conclusions

  3. 2013 May 4-7 Understanding the User Development Stage ??? Personal Judgement Audio Processor

  4. 2013 May 4-7 Evaluation Procedures • ObjectiveIndexes • PsychoacusticModels • SubjectiveTests

  5. 2013 May 4-7 ClassicalApproach

  6. Possible Enhanced Audio 2013 May 4-7 OurApproach

  7. 2013 May 4-7 Interactive EvolutionaryAlgorithm Subjective Evaluation «Reproduction» New Pool Selection Pool of PossibleSettings

  8. 2013 May 4-7 MainDrawbacks User Fatigue Time Constraint User Discrimination Partial Ordering Fast convergenceobtained with fewpossible fitness values

  9. 2013 May 4-7 OurProposal IEC hasbeenseldomlyusedin audio processing applications. Webelieveit to be of practicalinterest for a wide range of tasks. Thisis the mainreasonwe are proposingthisframework.

  10. 2013 May 4-7 Applications – Games Audio for Games

  11. 2013 May 4-7 Applications – Forensic Audio Forensic Audio (Image property of SoundAndSound)

  12. 2013 May 4-7 Applications – Immersive Experience Immersive Audio (Image property of Integrated Media Systems Center)

  13. 2013 May 4-7 Interactive AEC

  14. 2013 May 4-7 Test Setup Five signalsdistorted by female voice. Echocancellationthroughaffine projectionalgorithm (APA) with 4 parameters. A standard GA minimizesnormalizedmisalignment: An IGA shouldminimizeuser’spreferences.

  15. 2013 May 4-7 Test Setup - Workflow OriginalSignals Standard Minimization IEC Minimization Set 2 Set 1 SubjectiveComparison

  16. 2013 May 4-7 Results

  17. 2013 May 4-7 Conclusions Goodresults of ourframework on AEC. User fatigueis the maindrawback to be confronted. Severalapplicationsawaits in the future. Possiblecombination of objective and subjectivemeasurements.

  18. Thanks for yourattention!simone.scardapane@uniroma1.it

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