This algorithm implements the Maximum-a-posteriori (MAP) estimation
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The code for this algorithm in Python
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For a given set of feature vectors and a Gaussian Mixture Models (GMM), this algorithm implements the Maximum-a-posteriori (MAP) estimation (adapting only the means).
Details of MAP estimation can be found in the paper: Reynolds, Douglas A., Thomas F. Quatieri, and Robert B. Dunn. "Speaker verification using adapted Gaussian mixture models." Digital signal processing 10.1 (2000): 19-41. A very good description on how the MAP estimation works can be found in the Mathematical Monks's YouTube channel.z
This algorithm relies on the Bob library.