A class for Gaussian Mixture Model storage. For more details about Gaussian Mixture Models (GMM) you can refer to [Bimbot04].
Attr w: | array of weight parameters |
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Attr mu: | ndarray of mean parameters, each line is one distribution |
Attr invcov: | ndarray of inverse co-variance parameters, 2-dimensional for diagonal co-variance distribution 3-dimensional for full co-variance |
Attr invchol: | 3-dimensional ndarray containing lower cholesky decomposition of the inverse co-variance matrices |
Attr cst: | array of constant computed for each distribution |
Attr det: | array of determinant for each distribution |
Expectation-Maximization estimation of the Mixture parameters.
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Return llk: | a list of log-likelihoods obtained after each iteration |
Expectation-Maximization estimation of the Mixture parameters.
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Return llk: | a list of log-likelihoods obtained after each iteration |
Compute log posterior probabilities for a set of feature frames.
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Returns: | A ndarray of log-posterior probabilities corresponding to the input feature set. |
Return the dimension of distributions of the Mixture
Returns: | an integer, size of the acoustic vectors |
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Return the number of distribution of the Mixture
Returns: | the number of distribution in the Mixture |
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Return Inverse covariance super-vector
Returns: | an array, super-vector of the inverse co-variance coefficients |
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Return mean super-vector
Returns: | an array, super-vector of the mean coefficients |
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Read a Mixture in alize raw format
Parameters: | mixtureFileName – name of the file to read from |
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Read a Mixture in HTK format
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Read IdMap in PICKLE format.
Parameters: | inputFileName – name of the file to read from |
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Save a mixture in alize raw format
Parameters: | mixtureFileName – name of the file to write in |
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Save a Mixture in HTK format
Parameters: | mixtureFileName – the name of the file to write in |
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Save Ndx in PICKLE format. Convert all data into float32 before saving, note that the conversion doesn’t apply in Python 2.X
Parameters: | outputFilename – name of the file to write to |
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Return the dimension of the super-vector
Returns: | an integer, size of the mean super-vector |
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