User:Icax0r/Maximum likelihood linear regression
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Maximum Likelihood Linear Regression (also known as MLLR) is a commonly-used technique in Speech recognition for speaker adaptation. Given a small amount of speech from a target speaker, the parameters of a speaker-independent model can be adjusted to maximize the likelihood of the target speaker's speech under the model.
Description[edit]
Parameter Tying[edit]
If not all of the distributions are observed in the training data, then the parameters may be tied - i.e. a single transformation matrix is applied to several distributions. Distributions can be clustered according to phonetic similarity, or automatic clustering methods may be used.
-- TODO -- math
Relation to Other Types of Adaptation[edit]
CMLLR[edit]
-- TODO -- doesn't rely on having a transcript. and MLLR does?? use a GMM to estimate the tr
MAP Adaptation[edit]
-- TODO you need more data. --
References[edit]
External links[edit]