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# Run Language Identification

The process of running language identification tasks is very similar regardless of which mode it is run in. As such, the bulk of this section focuses on segmented identification, with significant differences for other modes described where appropriate.

To identify the languages in streamed audio, use the `LangId` task, with `LIDMode` set to the appropriate language identification mode. For more information about this standard tasks, see the IDOL Speech Server Reference.

Use the following procedure to identify the languages in an audio file.

To identify languages in an audio file

1. Create a list that contains the file names (including file extensions) of the classifiers to use.

   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 `LangId`.
   `LidMode` | The mode to use. Set to `Segmented` for segmented mode (this is the default), `Boundary` for boundary mode, or `Cumulative` for cumulative mode.
   `File` | The audio file to process. To restrict processing to a section of the audio file, set the `StartTime` and `EndTime` parameters. For more information, see the IDOL Speech Server Reference).
   `Out` | The file to write the language identification results to.

   - If you want to change the audio sample rate, or if you want to use your own custom classifiers, you must also set the `ClassList` parameter. You might also need to specify the `ClassPath` parameter, depending on the location of the classifier files. See the IDOL Speech Server Reference for more information.

   - If you use the base classifier pack, set the languages that you want to identify in the `LangList` configuration parameter in the `langid` module.

   - If you want to use open set language identification, you must also set the `ClosedSet` parameter to `False`. For more information about open set language identification, see Open Set Language Identification and the IDOL Speech Server Reference.

For example:

    http://localhost:15000/action=AddTask&Type=LangId&LIDMode=Segmented&File=C:\Data\Speech.wav&ClassList=ListManager\OptClassSet&ClassPath=C:\LangID\&Out=SpeechLang1.ctm

This action identifies languages in the `Speech.wav` file using the language classifiers specified in the `OptClassSet` list, and writes the identification results to the `SpeechLang1.ctm` file.

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 file. See Find Recommended Language Resources to Use in a Task.

IDOL Speech Server displays the results in XML format in your web browser. You can also open the .ctm file from the configured IDOL Speech Server temporary directory (or another location if you specified a path in the `Out` parameter).

The following is an example of the .ctm output produced by the `LangId` task in `Segmented` mode.

`1` | `L1` | `0.00` | `30.58` | `English` | `1.000` | `1.252`
`1` | `L2` | `0.00` | `30.58` | `German` | `0.686` | `1.252`
`1` | `L3` | `0.00` | `30.58` | `French` | `0.550` | `1.252`
`1` | `L1` | `30.58` | `28.30` | `German` | `1.000` | `1.306`
`1` | `L2` | `30.58` | `28.30` | `English` | `0.562` | `1.306`
`1` | `L3` | `30.58` | `28.30` | `Italian` | `0.517` | `1.306`
`1` | `L1` | `58.88` | `31.12` | `English` | `1.000` | `1.295`
`1` | `L2` | `58.88` | `31.12` | `French` | `0.680` | `1.295`
`1` | `L3` | `58.88` | `31.12` | `German` | `0.511` | `1.295`

From left to right, the columns in the .ctm file contain:

- The channel ID (usually `1`)
- The ranking of the language result at this time (`L1` is the top result, `L2` the next best, and so on)
- The start time of the processed segment in seconds
- The duration of the processed segment in seconds
- The identified language
- The score for this language (if normalized scores are being used, this score ranges from `0.0` to `1.0`; otherwise a log score is reported)
- The confidence for the highest-ranked decision in the current segment (`1.0` and above–the higher the score, the more confident the system is that `L1` is the correct answer)

The example shows a 90-second file being recognized in segments, each approximately 30 seconds in duration. For the first segment, English is the language that is identified as being the most likely (`L1`), followed by German (`L2`) and French (`L3`). For the next segment, German has the highest confidence score. For the final segment, English has the highest confidence score again.

In `Segmented` mode, it is common to see different results for each segment, because the language might change throughout the file. `Cumulative` mode assesses the most dominant language across the whole file, so you would not expect to see these changes.

The following example shows some of the same information displayed in XML format.

    <lid_transcript>
    	<lid_record>
    		<start>0.000</start>
    		<end>30.580</end>
    		<label>English</label>
    		<score>1.000</score>
    		<confidence>1.252</confidence>
    		<rank>1</rank>
    	</lid_record>
    	<lid_record>
    		<start>0.000</start>
    		<end>30.580</end>
    		<label>German</label>
    		<score>0.686</score>
    		<confidence>1.252</confidence>
    		<rank>2</rank>
    	</lid_record>
    </lid_transcript>

This output format is common to the `Segmented` and `Cumulative` modes. The output format for `Boundary` mode is similar, but the time points occur whenever a language change is detected, instead of after a fixed time period.

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