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# Build the Language Model

After you have selected and prepared the training text files, you can build the custom language model.

To build the language model

1. Create a list that contains the file names (including file extensions) of all training text files. You do not have to include the file paths because you can use the `DataPath` parameter to specify the directory path in the next step.

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

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

   `Type` | The task name. Set to `LanguageModelBuild`.
   `DataList` | The list that specifies the training text files.
   `DataPath` | The path to the directory that contains the files specified in the `DataList` parameter.
   `KeepList` | The path to a file that contains a list of words that the language model must contain. For more information on the format of the file, see the HPE IDOL Speech Server Reference.
   `Lang` | The language pack to use as a base (for example, `ENUK-tel`).
   `NewLanguageModel` | The name to give the custom language model that is generated.
   `NewLmInfoFile` | The output Language Model Information file name. If you do not set this parameter, the file has the same as the generated language model (and is located in the same directory), but with the extension `.lmi` instead of `.tlm`. Note: You can use the `GetResults` action to retrieve the `.lmi` file by setting the `Label` parameter to `lmi`.
   `NewDictionary` | The name of the dictionary to generate; usually it is the same value as `NewLanguageModel`. Note: If you do not set the `NewDictionary` parameter, Speech Server uses the output language model file name specified as the value of the `NewLanguageModel` parameter, but with the extension `.dct.sz` rather than `.tlm`.
   `DoSmoothing` | If you are using a custom language model for a transcript alignment task, set `DoSmoothing` to `False`. Otherwise, you can use the default value of `True`.

   If the training text files contain Japanese, Korean, Mandarin, or Taiwanese Mandarin languages, set the `DoSegment` parameter.

   `DoSegment` | Set to `True` to enable text segmentation.

For example:

`http://localhost:13000/action=AddTask&Type=LanguageModelBuild&KeepList=ListManager/KeepWordsList.txt&DataList=ListManager/Langmodel&DataPath=C:\LanguageModelFiles&Lang=ENUK-tel&NewLanguageModel=mymodel.tlm&NewDictionary=mymodel.dct.sz`

This action uses port `13000` to instruct HPE IDOL Speech Server, which is located on the local machine, to use the training text specified in the `Langmodel` list and the `ENUK-tel` language pack to build a new language model and dictionary file, both named `mymodel`. The language model that the task produces must contain the words in the `KeepWordsList` text file. This action also calculates a recommended interpolation weight at the end of the language model building process.

Note: The interpolation weight is only a suggested weight–you can choose to set other weights.

The new language models are placed in the custom language models folder that is specified by the `CustomLmDir` parameter in the HPE IDOL Speech Server configuration file.

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

- Check the task status. See Check the Status of a Task.
- Send the `GetResults` action to retrieve the recommended interpolation weight for the custom language model. See Find Recommended Language Resources to Use in a Task.

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