1. dataformats
  2. pkorshunov
  3. two-classes-gmm
  4. 1

Forked from tutorial/gmm/1

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{
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    "model_one": {
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        "variances": [
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            0,
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            0,
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            "float64"
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        ],
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        "#description": "First model Gaussian-Mixture Model object",
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        "variance_thresholds": [
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            0,
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            0,
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            "float64"
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        ],
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        "weights": [
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            0,
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            "float64"
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        ],
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        "means": [
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            0,
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            0,
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            "float64"
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        ]
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    },
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    "model_two": {
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        "variances": [
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            0,
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            0,
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            "float64"
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        ],
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        "#description": "Second model Gaussian-Mixture Model object",
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        "variance_thresholds": [
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            0,
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            0,
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            "float64"
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        ],
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        "weights": [
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            0,
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            "float64"
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        ],
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        "means": [
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            0,
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            0,
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            "float64"
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        ]
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    }
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}

The JSON descriptor for this object
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Container for Gaussian Mixture Models (GMM). This container stores:

  • means: The means of each gaussian component.
  • variances: The variances of each gaussian component.
  • weights: The weights of each gaussian component.
  • variance_thresholds: The variance flooring for each gaussian component.

Specific details can be found in [Reynolds2000].

[Reynolds2000]
  1. Reynolds, T. Quatieri, R. Dunn: Speaker verification using adapted Gaussian mixture models. Digital signal processing 10.1 (2000): 19-41.
Updated Name Actions
April 3, 2016 pkorshunov/gmm-two-models-projection-train/2 (Bob 2.0 projection of features on GMM model. Input id is a string.)
1
April 2, 2016 pkorshunov/gmm-two-models-projection/3 (Bob 2.0 projection of features on GMM model. Input id is a string.)
2
April 1, 2016 pkorshunov/gmm-spoofing/4 (Bob 2.0 training of two GMMs for two types of features)
2
Created with Raphaël 2.1.2[compare]tutorial/gmm/1pkorshunov/two-classes-gmm/12014Jun232016Apr1
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