This algorithm implements the Maximum-a-posteriori (MAP) estimation for a GMM
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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).
This algorithm relies on the Bob library.
The inputs are:
The output, model, is the adapted GMM (MAP adaptation).
|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.