Bob 2.0 projection of features on GMM model. Input id is a string.

This algorithm is a legacy one. The API has changed since its implementation. New versions and forks will need to be updated.
This algorithm is splittable

Algorithms have at least one input and one output. All algorithm endpoints are organized in groups. Groups are used by the platform to indicate which inputs and outputs are synchronized together. The first group is automatically synchronized with the channel defined by the block in which the algorithm is deployed.

Group: main

Endpoint Name Data Format Nature
features system/array_2d_floats/1 Input
scores system/float/1 Output

Unnamed group

Endpoint Name Data Format Nature
classifier pkorshunov/two-classes-gmm/1 Input

The code for this algorithm in Python
The ruler at 80 columns indicate suggested POSIX line breaks (for readability).
The editor will automatically enlarge to accomodate the entirety of your input
Use keyboard shortcuts for search/replace and faster editing. For example, use Ctrl-F (PC) or Cmd-F (Mac) to search through this box

For a given set of feature vectors and a Gaussian Mixture Models (GMM), this algorithm implements the Maximum-a-posteriori (MAP) estimation (adapting only the means).

Details of MAP estimation can be found in the paper: Reynolds, Douglas A., Thomas F. Quatieri, and Robert B. Dunn. "Speaker verification using adapted Gaussian mixture models." Digital signal processing 10.1 (2000): 19-41. A very good description on how the MAP estimation works can be found in the `Mathematical Monks's <>`_ YouTube channel.z

This algorithm relies on the `Bob <>`_ library.

Docutils System Messages

System Message: ERROR/3 (<string>, line 3); backlink

Unknown target name: "mathematical monks&amp;#39;s &amp;lt;;amp;index=31&amp;amp;list=pld0f06aa0d2e8ffba&amp;amp;spfreload=1&amp;gt;".

System Message: ERROR/3 (<string>, line 6); backlink

Unknown target name: "bob &amp;lt;;gt;".


Updated Name Databases/Protocols Analyzers
pkorshunov/pkorshunov/isv-asv-pad-fusion-complete/1/asv_isv-pad_gmm-fusion_lr-pa avspoof/2@physicalaccess_verify_train,avspoof/2@physicalaccess_verification,avspoof/2@physicalaccess_verification_spoof,avspoof/2@physicalaccess_verify_train_spoof,avspoof/2@physicalaccess_antispoofing pkorshunov/spoof-score-fusion-roc_hist/1
pkorshunov/pkorshunov/speech-pad-simple/1/speech-pad_gmm-pa avspoof/2@physicalaccess_antispoofing pkorshunov/simple_antispoofing_analyzer/4

This table shows the number of times this algorithm has been successfully run using the given environment. Note this does not provide sufficient information to evaluate if the algorithm will run when submitted to different conditions.

Terms of Service | Contact Information | BEAT platform version 2.2.1b0 | © Idiap Research Institute - 2013-2024