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METHODS, APPARATUS AND SYSTEMS FOR INDIVIDUALIZING AUDIO, MUSIC AND SPEECH ADAPTIVELY, INTELLIGENTLY AND INTERACTIVELY

  • US 20140169572A1
  • Filed: 12/19/2012
  • Published: 06/19/2014
  • Est. Priority Date: 12/19/2012
  • Status: Active Grant
First Claim
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1. A sound individualizing system, comprising the steps of:

  • (a) adjusting a sound by an automatic fluctuation control unit;

    (b) performing operations of windowing through a windowing unit and padding a plurality of zeros by a zero padding unit;

    (c) transforming a first output of said zero padding unit into a plurality of time-frequency bins by a forward transform unit;

    (d) passing said time-frequency bins through a cepstrum calculation unit to output a cepstrum;

    (e) processing said cepstrum by at least one cepstrum-domain lifter;

    (f) conveying a second output of said lifter into an adaptive classification unit;

    (g) directing a third output of said forward transform unit to a weighted fusion unit, wherein said weighted fusion unit merges said adjacent time-frequency bins according to human auditory scaling;

    (h) employing a fourth output of said weighted fusion unit by a long-term moment calculation unit, wherein said long-term moment calculation unit computes a plurality of long-term variance, skewness, kurtosis and higher-order moments;

    (i) conveying said fourth output of said weighted fusion unit to a short-term moment calculation unit, wherein said short-term moment calculation unit computes a plurality of short-term variance, skewness, kurtosis and higher-order moments;

    (j) directing said long-term and short-term variances, skewnesses, kurtosises and higher-order moments to said adaptive classification unit;

    (k) passing said fourth output of said weighted fusion unit to a multi-block weighted averaging unit, wherein said multi-block weighted averaging unit suppresses a plurality of undesired components;

    (l) calculating a fifth output and a sixth output, wherein said fifth output is a long-term mean value and said sixth output is a short-term mean value;

    (m) sending said long-term and short-term mean values to said adaptive classification unit, wherein said adaptive classification unit utilizes said cepstrum vector, said long-term and short-term mean values, variances, skewnesses, kurtosises and higher-order moments to classify said sound into a beat category and a non-beat category;

    (n) converting said beat category and said non-beat category to a beat signal;

    (o) updating said automatic fluctuation control unit, said windowing unit, and said weighting coefficients, wherein said updated weighting coefficients control said multi-block weighted averaging unit to compute said long-term and short-term mean values; and

    (p) employing said beat signal to enhance auditory perception of an individual listener by an individualized auditory enhancer in accordance to a human input unit.

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