[sphinx] Fixed sphinx doc

[conda] Added the test requirements

[conda] Added voicePA as test requirement
parent d19da69c
Pipeline #16536 passed with stage
in 15 minutes and 3 seconds
......@@ -54,6 +54,11 @@ test:
- coverage
- sphinx
- sphinx_rtd_theme
- gridtk
- bob.db.mobio
- bob.db.avspoof
- bob.db.asvspoof
- bob.db.voicepa
about:
home: https://www.idiap.ch/software/bob/
......
......@@ -63,15 +63,15 @@ The Algorithms
The algorithms present a set of state-of-the-art speaker recognition algorithms. Here is the list of short-cuts:
* ``gmm``: *Gaussian Mixture Models* (GMM) `[Rey00]`.
* ``gmm``: *Gaussian Mixture Models* (GMM) [Rey00]_.
- algorithm : :py:class:`bob.bio.gmm.algorithm.GMM`
* ``isv``: As an extension of the GMM algorithm, *Inter-Session Variability* (ISV) modeling `[Vogt08]` is used to learn what variations in samples are introduced by identity changes and which not.
* ``isv``: As an extension of the GMM algorithm, *Inter-Session Variability* (ISV) modeling [Vogt08]_ is used to learn what variations in samples are introduced by identity changes and which not.
- algorithm : :py:class:`bob.bio.gmm.algorithm.ISV`
* ``ivector``: Another extension of the GMM algorithm is *Total Variability* (TV) modeling `[Dehak11]` (aka. I-Vector), which tries to learn a subspace in the GMM super-vector space.
* ``ivector``: Another extension of the GMM algorithm is *Total Variability* (TV) modeling [Dehak11]_ (aka. I-Vector), which tries to learn a subspace in the GMM super-vector space.
- algorithm : :py:class:`bob.bio.gmm.algorithm.IVector`
......
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