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# Tune Parameters

You can set additional parameters in the tasks configuration file to improve the performance of speech-to-text.

## Noisy Data

If the audio data contains a lot of background noise or foreground music, you can enable speech detection to improve speech-to-text rates:

- In the `[frontend]` module used by the speech-to-text task, set the `DetectSpeech` parameter to `True` to modify how the speech-to-text engine processes audio sections that are labeled as speech, which can improve recognition in these sections.
- In the `[normalizer]` module used by the speech-to-text task, set `ZeroSilFrames` to `True`. The speech-to-text engine skips over sections of audio that are identified as silence.

## Missing Words in Transcript

If many of the words in the audio do not appear in the transcript, the language model might be too strongly weighted. In the language pack section of the configuration file, experiment with the following parameters:

- Lower the weighting of the `LmScale` parameter (the recommended range is between `0.2` and `2.0`).
- Raise the weighting of the `LmOffset` parameter (the recommended range is between `-0.5` and `+0.5`).

## Extra Words in Transcript

If the speech-to-text is producing many more words in the transcript file than are spoken in the audio, the language model might be too weakly weighted. In the language pack section of the tasks configuration file, experiment with the following parameters:

- Raise the `LmScale` parameter (the recommended range is between `0.2` and `2.0`).
- Lower the `LmOffset` parameter (the recommended range is between `-0.5` and `+0.5`.

You can also tune the following speech-to-text parameters to improve general speech-to-text performance :

- `Mode`
- `ModeValue`

For more information about these parameters, see the HPE IDOL Speech Server Reference.

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