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# Finalize the Adapted Acoustic Model

After IDOL Speech Server processes the adaptation data set, you have one or more accumulator files, depending on whether you split the adaptation data set into smaller chunks during the training processes. The final stage in adapting an acoustic model is to apply all the accumulator files to the original model.

To finalize the adapted acoustic model

1. Create a list that contains the file names (excluding file extensions and paths) of all accumulator files (see Data Naming Scheme). Create a list even if you have only one accumulator file.

   For more information about IDOL Speech Server's list manager, see Create and Manage Lists.

2. Send an `AddTask` action to IDOL Speech Server, and set the following parameters:

   `Type` | The task name. Set to `AmTrainFinal`.
   `InAm` | The acoustic model file to adapt.
   `AccList` | The list that specifies the accumulator files.
   `AccPath` | The path to the directory that contains the accumulator files.
   `OutAm` | The name of the adapted acoustic model to create.

For example:

    http://localhost:13000/action=AmTrainFinal&InAm=C:\LP\ENUK\ver-ENUK-5.0-16k.am&AccList=ListManager/accList&AccPath=C:\AMTRAIN\acc&OutAm=myModel.am

This action uses port `13000` to instruct IDOL Speech Server, which is located on the local machine, to apply the accumulators stored in `C:\AMTRAIN\acc` to the `ver-ENUK-5.0-16k` acoustic model to produce the adapted acoustic model `myModel.am`.

This action returns a token. You can use the token to:

- Check the task status. See Check the Status of a Task.
- Retrieve the results. See Find Recommended Language Resources to Use in a Task.

You can set the following parameters to further configure the adaptation operation.

`Relevance` | How much relevance to give to the original model parameters when updating the means and variances of the 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 more examples are needed in the adaptation data for the model to change significantly. If you are running the `AmTrain` task in rapid adaptation mode, HPE recommends that you set the `Relevance` parameter to `0` (zero). Any other value limits the effectiveness of the adaptation process.
`MinEgs` | The minimum number of examples (frames) that have to have been seen for a specific model parameter to be updated.

For more information about the `[amadaptend]` module parameters, see the IDOL Speech Server Reference.

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