diff --git a/doc/guide_chrom.rst b/doc/guide_chrom.rst
index 8d2714467d9f766aa90cafa0e1f61bdd76430752..72ce4a20c6044cc014771f23a9307684b0140cf3 100644
--- a/doc/guide_chrom.rst
+++ b/doc/guide_chrom.rst
@@ -94,11 +94,11 @@ given below.
    The execution of this script is very slow - mainly due to the face detection. 
    You can speed it up using the gridtk_ (especially, if you're at Idiap). For example::
 
-     $ ./bin/jman sub -t 3490 -- ./bin/bob_rppg_chrom_pulse.py cohface
+     $ ./bin/jman sub -t 3490 -- ./bin/bob_rppg_chrom_pulse.py config.py
 
    The number of jobs (i.e. 3490) is given by typing::
      
-     $ ./bin/bob_rppg_chrom_pulse.py cohface --gridcount
+     $ ./bin/bob_rppg_chrom_pulse.py config.py --gridcount
 
 
 .. _gridtk: https://pypi.python.org/pypi/gridtk
diff --git a/doc/guide_cvpr14.rst b/doc/guide_cvpr14.rst
index 5dd152d4944e64e6aa89ccedd6e6a35f61b35688..0ae80b3c72d5f272a901fd075645b539b6aa6959 100644
--- a/doc/guide_cvpr14.rst
+++ b/doc/guide_cvpr14.rst
@@ -84,7 +84,7 @@ the command-line overrides the configuration file though.
 
    The number of jobs (i.e. 3490) is given by typing::
      
-     $ ./bin/bob_rppg_cvpr14_extract_face_and_bg_signals.py cohface --gridcount
+     $ ./bin/bob_rppg_cvpr14_extract_face_and_bg_signals.py config.py --gridcount
 
 
 Step 2: Illumination Rectification
@@ -113,8 +113,8 @@ channel on all the segment of all sequences. By default, the threshold is set su
 of all the segments will be retained. To get the signals where large motion has
 been eliminated, execute the following commands::
 
-  $ ./bin/bob_rppg_cvpr14_motion.py cohface --save-threshold threshold.txt -vv
-  $ ./bin/bob_rppg_cvpr14_motion.py cohface --load-threshold threshold.txt -vv
+  $ ./bin/bob_rppg_cvpr14_motion.py config.py --save-threshold threshold.txt -vv
+  $ ./bin/bob_rppg_cvpr14_motion.py config.py --load-threshold threshold.txt -vv
 
 
 Step 4: Filtering
@@ -129,7 +129,7 @@ window. Finally, a bandpass filter is applied to restrict the
 frequencies to the range corresponding to a plausible heart-rate. To filter the
 signal, you should execute the following command::
 
-  $ ./bin/bob_rppg_cvpr14_filter.py cohface -vv
+  $ ./bin/bob_rppg_cvpr14_filter.py config.py -vv
 
 A Full Configuration File Example
 ---------------------------------
diff --git a/doc/guide_ssr.rst b/doc/guide_ssr.rst
index d4237ab135d80218f4583f89a996d9e19a5f8ef0..090ee6632ded291339e4dad012ed61e581c1491a 100644
--- a/doc/guide_ssr.rst
+++ b/doc/guide_ssr.rst
@@ -86,11 +86,11 @@ given below.
    The execution of this script is very slow - mainly due to the face detection. 
    You can speed it up using the gridtk_ (especially, if you're at Idiap). For example::
 
-     $ ./bin/jman sub -t 3490 -- ./bin/bob_rppg_ssr_pulse.py cohface
+     $ ./bin/jman sub -t 3490 -- ./bin/bob_rppg_ssr_pulse.py config.py
 
    The number of jobs (i.e. 3490) is given by typing::
      
-     $ ./bin/bob_rppg_ssr_pulse.py cohface --gridcount
+     $ ./bin/bob_rppg_ssr_pulse.py config.py --gridcount
 
 
 .. _gridtk: https://pypi.python.org/pypi/gridtk