10 ,FIG. 3 .
103a posterior (MAP) estimation of model parameters is central in bayesian statistics. In this setting prior 28 Digital Signal Processing Vol. NosPictorial example of two steps in adapting a hypothesized speaker model. (a) The training vectors (x's) are probabilistically mapped into the UBM mixtures. (b) The adapted mixture parameters are derived using the statistics of the new **data** and the UBM mixture parameters. The adaptation is **data** dependent, so UBM mixture parameters are adapted by different amounts.
