Hello,
One possibility is to use the xbob.db.verification.filelist
package.
Spear runs a complete evaluation on a specific dataset.
This xbob.db.verification.filelist package allows you to use your
own customized lists for training, speaker enrollment and probing.
Inside the spear package, you have examples on how to define such
lists, e.g.:
https://github.com/bioidiap/spear/tree/master/protocols/timit/2
In your case, you will have to:
1. Put the trained background model at the location spear is
supposed to generate it. This way it won't be regenerated and only
used for the next processing steps.
2. Define your customized lists: in the 'dev' (cf.
https://github.com/bioidiap/spear/tree/master/protocols/timit/2/dev)
directory,
2.a. create the 'for_models.lst' with the file(s) you want to
use for speaker enrollment and
2.b. create the 'for_scores.lst' with the file(s) you want to
use for probing the speaker model(s)
3. Create a configuration file for this database (e.g.:
https://github.com/bioidiap/spear/blob/master/config/database/timit.py)
4. Run spear using this database configuration file and selecting
the output directories, such as the pre-trained background model
can be successfully read.
Cheers,
Laurent