Package org.vocvark.DataTypes

Examples of org.vocvark.DataTypes.FeatureDefinition

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        String name = "Strongest Frequency Via Zero Crossings";
        String description = "The strongest frequency component of a signal, in Hz, " +
                "found via the number of zero-crossings.";
        boolean is_sequential = true;
        int dimensions = 1;
        definition = new FeatureDefinition(name,
                description,
                is_sequential,
                dimensions);

        dependencies = new String[1];
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        String description = "The standard deviation of the frequency of the" +
                "power spectrum bin with the highest power over" +
                "the last 100 windows.";
        boolean is_sequential = true;
        int dimensions = 1;
        definition = new FeatureDefinition(name,
                description,
                is_sequential,
                dimensions);

        int number_windows = 100;
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     * offsets) of this feature.
     */
    public RelativeDifferenceFunction() {
        String name = "Relative Difference Function";
        String decsription = "log of the derivative of RMS.  Used for onset detection.";
        definition = new FeatureDefinition(name, decsription, true, 1);
        dependencies = new String[]{"Root Mean Square", "Root Mean Square"};
        offsets = new int[]{0, -1};
    }
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        String name = "Strength Of Strongest Beat";
        String description = "How strong the strongest beat in the beat histogram " +
                "is compared to other potential beats.";
        boolean is_sequential = true;
        int dimensions = 1;
        definition = new FeatureDefinition(name,
                description,
                is_sequential,
                dimensions);

        dependencies = new String[2];
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        String name = "Strongest Frequency Via FFT Maximum";
        String description = "The strongest frequency component of a signal, in Hz, " +
                "found via finding the FFT bin with the highest power.";
        boolean is_sequential = true;
        int dimensions = 1;
        definition = new FeatureDefinition(name,
                description,
                is_sequential,
                dimensions);

        dependencies = new String[2];
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    public RMS() {
        String name = "Root Mean Square";
        String description = "A measure of the power of a signal.";
        boolean is_sequential = true;
        int dimensions = 1;
        definition = new FeatureDefinition(name,
                description,
                is_sequential,
                dimensions);

        dependencies = null;
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    public LPC() {
        String name = "LPC";
        String description = "Linear Prediction Coeffecients calculated using autocorrelation and Levinson-Durbin recursion.";
        String[] attributes = new String[]{"lambda for frequency warping",
                "number of coeffecients to calculate"};
        definition = new FeatureDefinition(name, description, true, 10,
                attributes);
        dependencies = null;
        offsets = null;
    }
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        } else {
            numDimensions = n;
            String name = definition.name;
            String description = definition.description;
            String[] attributes = definition.attributes;
            definition = new FeatureDefinition(name, description, true, numDimensions, attributes);

        }
    }
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    public MagnitudeSpectrum() {
        String name = "Magnitude Spectrum";
        String description = "A measure of the strength of different frequency components.";
        boolean is_sequential = true;
        int dimensions = 0;
        definition = new FeatureDefinition(name,
                description,
                is_sequential,
                dimensions);

        dependencies = null;
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     */
    public MFCC() {
        String name = "MFCC";
        String description = "MFCC calculations based upon Orange Cow code";
        String[] attributes = new String[]{"Number of Coeffecients"};
        definition = new FeatureDefinition(name, description, true, 13, attributes);
        dependencies = new String[]{"Magnitude Spectrum"};
        offsets = new int[]{0};
        fe = new featureExtraction();
    }
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Related Classes of org.vocvark.DataTypes.FeatureDefinition

  • org.vocvark.Aggregators.AreaMoments
  • org.vocvark.Aggregators.AreaPolynomialApproximation
  • org.vocvark.Aggregators.DummyAgg
  • org.vocvark.Aggregators.Mean
  • org.vocvark.Aggregators.MFCC
  • org.vocvark.Aggregators.MultipleFeatureHistogram
  • org.vocvark.Aggregators.StandardDeviation
  • org.vocvark.AudioFeatures.AreaMoments
  • org.vocvark.AudioFeatures.BeatHistogram
  • org.vocvark.AudioFeatures.BeatHistogramLabels
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