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Concept of a Time Frequency Masking Model based on Gabor ...Peter Balazs (ARI) Multipliers & Masking...

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Concept of a Time Frequency Masking Model based on Gabor filters and 2D convolution Peter Balazs Acoustics Research Institute (ARI) Austrian Academy of Sciences in cooperation with: NuHAG Vienna LATP, CMI & LMA, CNRS Marseille FYMA, UCL Louvain-La-Neuve Amade workshop 05.10.2006 Peter Balazs (ARI) Multipliers & Masking 1 / 24
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  • Concept of a Time Frequency Masking Model based onGabor filters and 2D convolution

    Peter Balazs

    Acoustics Research Institute (ARI)Austrian Academy of Sciences

    in cooperation with:NuHAG Vienna

    LATP, CMI & LMA, CNRS Marseille

    FYMA, UCL Louvain-La-Neuve

    Amade workshop05.10.2006

    Peter Balazs (ARI) Multipliers & Masking 1 / 24

  • Overview:

    1 IntroductionMP3

    2 Simultaneous Masking

    3 Gabor Filters

    4 Time Frequency Masking

    5 Current Research and Conclusion

    Peter Balazs (ARI) Multipliers & Masking 2 / 24

  • Overview:

    1 IntroductionMP3

    2 Simultaneous Masking

    3 Gabor Filters

    4 Time Frequency Masking

    5 Current Research and Conclusion

    Peter Balazs (ARI) Multipliers & Masking 2 / 24

  • Overview:

    1 IntroductionMP3

    2 Simultaneous Masking

    3 Gabor Filters

    4 Time Frequency Masking

    5 Current Research and Conclusion

    Peter Balazs (ARI) Multipliers & Masking 2 / 24

  • Overview:

    1 IntroductionMP3

    2 Simultaneous Masking

    3 Gabor Filters

    4 Time Frequency Masking

    5 Current Research and Conclusion

    Peter Balazs (ARI) Multipliers & Masking 2 / 24

  • Overview:

    1 IntroductionMP3

    2 Simultaneous Masking

    3 Gabor Filters

    4 Time Frequency Masking

    5 Current Research and Conclusion

    Peter Balazs (ARI) Multipliers & Masking 2 / 24

  • Application : MP3-Player

    • MP3• encoding / decoding scheme• MPEG1/MPEG2 (Layer 3)• signal processing• psychoacoustical model

    • Signal Processing• applications: mobile phone,

    UMTS, xDSL or digitaltelevision

    • engineering field• mathematical field

    • Psychoacoustic Masking

    Peter Balazs (ARI) Multipliers & Masking 3 / 24

  • Application : MP3-Player

    • MP3• encoding / decoding scheme• MPEG1/MPEG2 (Layer 3)• signal processing• psychoacoustical model

    • Signal Processing• applications: mobile phone,

    UMTS, xDSL or digitaltelevision

    • engineering field• mathematical field

    • Psychoacoustic Masking

    Peter Balazs (ARI) Multipliers & Masking 3 / 24

  • Application : MP3-Player

    • MP3• encoding / decoding scheme• MPEG1/MPEG2 (Layer 3)• signal processing• psychoacoustical model

    • Signal Processing• applications: mobile phone,

    UMTS, xDSL or digitaltelevision

    • engineering field• mathematical field

    • Psychoacoustic Masking

    Peter Balazs (ARI) Multipliers & Masking 3 / 24

  • Psychoacoustic Masking: introduction

    Masking:presence of one stimulus, the masker, decreases the response to anotherstimulus, the target.

    Irrelevance Filter: searches (and deletes) perceptional irrelevant data (incomplex signals) using a masking model, supposing that one audiocomponent masks the others.

    Typical Application:

    1 Sound / Data Compression

    2 Sound Design

    3 Background - Foreground Separation

    4 Improvement of Speech or Music Recognition

    Peter Balazs (ARI) Multipliers & Masking 4 / 24

  • Psychoacoustic Masking: introduction

    Masking:presence of one stimulus, the masker, decreases the response to anotherstimulus, the target.

    Irrelevance Filter: searches (and deletes) perceptional irrelevant data (incomplex signals) using a masking model, supposing that one audiocomponent masks the others.

    Typical Application:

    1 Sound / Data Compression

    2 Sound Design

    3 Background - Foreground Separation

    4 Improvement of Speech or Music Recognition

    Peter Balazs (ARI) Multipliers & Masking 4 / 24

  • Psychoacoustic Masking: introduction

    Masking:presence of one stimulus, the masker, decreases the response to anotherstimulus, the target.

    Irrelevance Filter: searches (and deletes) perceptional irrelevant data (incomplex signals) using a masking model, supposing that one audiocomponent masks the others.

    Typical Application:

    1 Sound / Data Compression

    2 Sound Design

    3 Background - Foreground Separation

    4 Improvement of Speech or Music Recognition

    Peter Balazs (ARI) Multipliers & Masking 4 / 24

  • Psychoacoustic Masking : existing algorithm I

    Existing algorithm in : simple model, but effective algorithm!Original audio file

    ”LossyCoding”

    Peter Balazs (ARI) Multipliers & Masking 5 / 24

    jumpref.wavMedia File (audio/wav)

  • Psychoacoustic Masking : existing algorithm II

    Existing algorithm in : simple model, but effective algorithm!Irrelevance Filter

    Original audio file

    ”Lossy Coding”

    Peter Balazs (ARI) Multipliers & Masking 6 / 24

    jumpmask.wavMedia File (audio/wav)

    jumpdiff.wavMedia File (audio/wav)

  • Psychoacoustic Masking : existing algorithm III

    Existing algorithm in : Original audio file (Spectrum)

    Peter Balazs (ARI) Multipliers & Masking 7 / 24

  • Psychoacoustic Masking : existing algorithm IV

    Existing algorithm in : Masked signal (Spectrum)

    Peter Balazs (ARI) Multipliers & Masking 8 / 24

  • Psychoacoustic Masking : existing algorithm V

    models simultaneousfrequency masking and usessingle spectra.

    It calculates an adaptive threshold function for the spectra, but works witha time-frequency analysis. This is an adaptive Gabor Filter withcoefficients in {0, 1}.With Gabor theory some properties are explained:

    • perfect reconstruction,• time frequency concentration,• smoothness and• numerical efficiency.

    Peter Balazs (ARI) Multipliers & Masking 9 / 24

  • Psychoacoustic Masking : existing algorithm V

    models simultaneousfrequency masking and usessingle spectra.

    It calculates an adaptive threshold function for the spectra, but works witha time-frequency analysis. This is an adaptive Gabor Filter withcoefficients in {0, 1}.With Gabor theory some properties are explained:

    • perfect reconstruction,• time frequency concentration,• smoothness and• numerical efficiency.

    Peter Balazs (ARI) Multipliers & Masking 9 / 24

  • Psychoacoustic Masking : psychoacoustical experiments

    Condition Correct Score1 68.6 %2 58.5 %3 50.5 %4 49.4 %

    Peter Balazs (ARI) Multipliers & Masking 10 / 24

  • Psychoacoustic Masking : temporal masking

    Also temporal masking exists:

    Temporal and frequency masking have been investigated a lot. But thereare only very few studies for time frequency behaviour.

    Goal: Investigate a true time-frequency masking model based on GaborFilters. Develop an efficient irrelevance algorithm!

    Peter Balazs (ARI) Multipliers & Masking 11 / 24

  • Psychoacoustic Masking : temporal masking

    Also temporal masking exists:

    Temporal and frequency masking have been investigated a lot. But thereare only very few studies for time frequency behaviour.

    Goal: Investigate a true time-frequency masking model based on GaborFilters. Develop an efficient irrelevance algorithm!

    Peter Balazs (ARI) Multipliers & Masking 11 / 24

  • Psychoacoustic Masking : temporal masking

    Also temporal masking exists:

    Temporal and frequency masking have been investigated a lot. But thereare only very few studies for time frequency behaviour.

    Goal: Investigate a true time-frequency masking model based on GaborFilters. Develop an efficient irrelevance algorithm!

    Peter Balazs (ARI) Multipliers & Masking 11 / 24

  • What is a Gabor Filter?

    Peter Balazs (ARI) Multipliers & Masking 12 / 24

  • Example for Gabor Filter = Gabor Multiplier

    Original audio file:

    Peter Balazs (ARI) Multipliers & Masking 13 / 24

    jump1.wavMedia File (audio/wav)

  • Example for Gabor Filter = Gabor Multiplier

    Symbol:

    Peter Balazs (ARI) Multipliers & Masking 14 / 24

  • Example for Gabor Filter = Gabor Multiplier

    Result of Gabor Multiplier.

    Peter Balazs (ARI) Multipliers & Masking 15 / 24

    result_jump1.wavMedia File (audio/wav)

  • Time Frequency Masking

    Peter Balazs (ARI) Multipliers & Masking 16 / 24

  • Psychoacoustic Masking : simultaneous masking I

    Existing Model, using bark scale

    Peter Balazs (ARI) Multipliers & Masking 17 / 24

  • Psychoacoustic Masking : simultaneous masking I

    Existing Model, using bark scale

    Peter Balazs (ARI) Multipliers & Masking 17 / 24

  • Psychoacoustic Masking : simultaneous masking I

    Existing Model, using bark scale

    Peter Balazs (ARI) Multipliers & Masking 17 / 24

  • Time Frequency Masking : using Gabor multipliers

    Simple concept for a time frequency masking model and algorithm:

    Convolution with Gabor transform ⇒ Symbol for Gabor Filter.Other, more complex 2D convolution kernels are possible!

    Peter Balazs (ARI) Multipliers & Masking 18 / 24

  • Time Frequency Masking : using Gabor multipliers

    Simple concept for a time frequency masking model and algorithm:

    Convolution with Gabor transform ⇒ Symbol for Gabor Filter.Other, more complex 2D convolution kernels are possible!

    Peter Balazs (ARI) Multipliers & Masking 18 / 24

  • Time Frequency Masking : using Gabor multipliers

    Simple concept for a time frequency masking model and algorithm:

    Convolution with Gabor transform ⇒ Symbol for Gabor Filter.Other, more complex 2D convolution kernels are possible!

    Peter Balazs (ARI) Multipliers & Masking 18 / 24

  • Time Frequency Masking : using Gabor multipliers

    Simple concept for a time frequency masking model and algorithm:

    Convolution with Gabor transform ⇒ Symbol for Gabor Filter.Other, more complex 2D convolution kernels are possible!

    Peter Balazs (ARI) Multipliers & Masking 18 / 24

  • Time Frequency Masking : using Gabor multipliers

    Simple concept for a time frequency masking model and algorithm:

    Convolution with Gabor transform ⇒ Symbol for Gabor Filter.Other, more complex 2D convolution kernels are possible!

    Peter Balazs (ARI) Multipliers & Masking 18 / 24

  • Current Research : psychoacoustical experiments

    Masking effect of time frequency atoms is important =⇒ Current research.

    =⇒ Sophie

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    300-msec Sinusoid3.3-msec Gaussian

    Peter Balazs (ARI) Multipliers & Masking 19 / 24

  • Current Research : psychoacoustical experiments

    Masking effect of time frequency atoms is important =⇒ Current research.=⇒ Sophie

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    2521 3181 4000 5015 6275 2521 3181 4000 5015 6275

    300-msec Sinusoid3.3-msec Gaussian

    Peter Balazs (ARI) Multipliers & Masking 19 / 24

  • Current Research

    Peter Balazs (ARI) Multipliers & Masking 20 / 24

  • Current Research

    • Investigate the mathematical and numerical background for a Gaborfilter further: (cooperation with NuHAG/LATP/UCL)

    • Bessel and frame multipliers• irregular Gabor multipliers• numerics of discrete Gabor analysis

    • Psychoacoustic experiment: (cooperation with LMA)• thresholds for Gaussian atoms• time frequency masking effects between two atoms• more complex sounds

    • Algorithms: (cooperation with LMA)• efficient implementation (real time)• experimental testing of its validity for different applications

    Peter Balazs (ARI) Multipliers & Masking 21 / 24

  • Current Research

    • Investigate the mathematical and numerical background for a Gaborfilter further: (cooperation with NuHAG/LATP/UCL)

    • Bessel and frame multipliers• irregular Gabor multipliers• numerics of discrete Gabor analysis

    • Psychoacoustic experiment: (cooperation with LMA)• thresholds for Gaussian atoms• time frequency masking effects between two atoms• more complex sounds

    • Algorithms: (cooperation with LMA)• efficient implementation (real time)• experimental testing of its validity for different applications

    Peter Balazs (ARI) Multipliers & Masking 21 / 24

  • Current Research

    • Investigate the mathematical and numerical background for a Gaborfilter further: (cooperation with NuHAG/LATP/UCL)

    • Bessel and frame multipliers• irregular Gabor multipliers• numerics of discrete Gabor analysis

    • Psychoacoustic experiment: (cooperation with LMA)• thresholds for Gaussian atoms• time frequency masking effects between two atoms• more complex sounds

    • Algorithms: (cooperation with LMA)• efficient implementation (real time)• experimental testing of its validity for different applications

    Peter Balazs (ARI) Multipliers & Masking 21 / 24

  • Conclusion

    • Gabor Filter Theory gives an insight on time-variantfiltering.

    • A simple Time Frequency Masking model exists.Further investigation starts at the time frequencyatom level .

    • A lot of interesting research, both applied andtheoretical, still has to be done.

    Peter Balazs (ARI) Multipliers & Masking 22 / 24

  • Conclusion

    • Gabor Filter Theory gives an insight on time-variantfiltering.

    • A simple Time Frequency Masking model exists.Further investigation starts at the time frequencyatom level .

    • A lot of interesting research, both applied andtheoretical, still has to be done.

    Peter Balazs (ARI) Multipliers & Masking 22 / 24

  • Conclusion

    • Gabor Filter Theory gives an insight on time-variantfiltering.

    • A simple Time Frequency Masking model exists.Further investigation starts at the time frequencyatom level .

    • A lot of interesting research, both applied andtheoretical, still has to be done.

    Peter Balazs (ARI) Multipliers & Masking 22 / 24

  • Personal References:

    P. Balazs, Regular and Irregular Gabor Multipliers with Application toPsychoacoustic Masking, PhD Thesis, Universität Wien (2005)

    P. Balazs, Basic Definition and Properties of Bessel Multipliers, Journal ofMathematical Analysis and Applications (in press, available online)

    P. Balazs, B. Laback, G. Eckel and W. A. Deutsch, Perceptional Sparsity bySimultaneous Masking, preprint

    P. Balazs, J.-P. Antoine, Weighted and controlled frames, submitted

    Peter Balazs (ARI) Multipliers & Masking 23 / 24

  • Thank you for your attention!

    Peter Balazs (ARI) Multipliers & Masking 24 / 24

    IntroductionMP3

    Simultaneous MaskingGabor FiltersTime Frequency MaskingCurrent Research and ConclusionReferences


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