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# WavSidTrain

Deprecated: The `WavSidTrain` task is deprecated for IDOL Server version 11.0.0. Use the `SpkIdTrainWav` task instead.

This task is still available for existing implementations, but it might be incompatible with new functionality. The task might be deleted in future.

The `WavSidTrain` task creates a speaker template from an audio file containing speech from a single speaker.

## Parameters

Parameter | Description | Required
--- | --- | ---
Type | The task name. Set to `WavSidTrain`. | Yes
Ast | The speaker classifier file. | See Comments.
Diag | Whether to generate diagnostic information. |
DiagFile | The file to write the diagnostic information to. |
File | The audio file containing sample speech from a single person. Aim to use a minimum of five minutes of speech. | Yes
MinFrames | The minimum number of speech audio frames required to train each component of a speaker model. |
NewModel | The speaker template file to create. | Yes
NMix | The number of components to create in the speaker model. |
Rel | The relevance to give to USM model parameters during adaptation. |
Sfreq | The sample frequency of the audio file to process. |
SidBase | The sid base pack resource to use to determine the base files to use. |
Sig | The .sig file to use for speaker identification. |
SugdInputChannels | The channel layout of the input media file. |
SugdInputFrequency | The sampling rate of the input media file. |
USM | The USM file to use. |
USMEnabled | Whether to use the USM as a base for speaker training. |

## Example

    http://localhost:13000/action=AddTask&Type=WavSidTrain&File=C:/Data/BobSpeech.wav&NewModel=Bob.spk

This action uses port `13000` to instruct IDOL Speech Server, which is located on the local machine, to create the `Bob.spk` template using the `BobSpeech.wav` file.

## Comments

If you do not specify the Ast parameter, the action uses the base ast file, determined by the SidBase resource. This base file does not contain any speaker information, and cannot identify speakers, but it performs gender detection and speaker segmentation.

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