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# Relevance

The relevance to assign the original model parameters when updating the means and variances of the original models. This effectively assigns a weight in frames to the original values, as if this number of frames had been seen during adaptation. The higher this number, the higher the number of examples seen in the adaptation data will have to be for the model to change significantly.

If you ran the `AmTrain` task in rapid adaptation mode, set the `Relevance` to `0` (zero). Any other value limits the effectiveness of the adaptation process.

Type: | Integer
Default: | 500
Range: | 0–128000
Required: | No
Configuration Section: | amadaptend module
Example: | `Relevance=1000`
See Also: | Relevance (action parameter)

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