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# FrameNorm

The frame normalization to use.

Set `FrameNorm` to one of the following options:

- `NONE`
- `UBM`
- `SET`
- `AUTO` (`audiotemplatescore` module only)

Note: The frame normalization used during the identification stage must match that used during development.

By default, Speech Server uses `UBM` if the templates are using a background model.

This means that when Speech Server generates scores for each audio frame, the server takes the background model score into account and subtracts the background model score from all the speaker scores. This process helps to reduce frame score variation (in cases where some frames might score higher on all models, including the background, leading to unstable results). HPE recommends that you use the `UBM` option for open-set speaker identification.

If you set `FrameNorm` to `NONE`, Speech Server does not take the background model score into account, but instead uses the scores as they are. HPE recommends that you use this option only if you trained your templates without using a Universal Background Model.

If you set `FrameNorm` to `SET`, Speech Server takes the scores for all templates, and normalizes them between 0.0 (the worst case) and 1.0 (the best case). This process can increase recall, but can also introduce more false hits. HPE recommends that you use the `SET` option for closed-set speaker identification.

If you set `FrameNorm` to `AUTO` in the `audiotemplatescore` module, Speech Server uses the frame normalization that was used during development when you produced the scores for threshold estimation. If development was not performed and there are no thresholds, Speech Server switches to `UBM` mode, unless you set `ClosedSet` to `True`, in which case Speech Server uses `SET` mode.

Action: | AddTask
Task: | SpkIdDevel , SpkIdDevelStream , SpkIdDevelWav
Type: | String
Default: | `UBM` in `audiotemplatedevel` module `AUTO` in `audiotemplatescore` module
Example: | `FrameNorm=SET`
See Also: | FrameNorm (configuration parameter)

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