diff --git a/doc/guide.rst b/doc/guide.rst
index 998ae5419aa224b39af113a2be401399e5b89366..d0d6b018754b50c96364ea2143e5f2fd53f76be0 100644
--- a/doc/guide.rst
+++ b/doc/guide.rst
@@ -346,8 +346,8 @@ The snippet bellow shows how to:
    >>> # Probing
    >>> probe_data = np.array([[1.2, 0.1, 1.4], [0.5, 0.2, 0.3]])
    >>> score = isv_machine.score_using_array(model, probe_data)
-   >>> print(score)
-     [2.754]
+   >>> print(round(score, 3))
+     2.754
 
 
 
@@ -407,8 +407,8 @@ such session variability model.
 
    >>> probe_data = np.array([[1.2, 0.1, 1.4], [0.5, 0.2, 0.3]])
    >>> score = jfa_machine.score_using_array(model, probe_data)
-   >>> print(score)
-     [0.471]
+   >>> print(round(score, 3))
+     0.471
 
 
 
diff --git a/src/bob/learn/em/factor_analysis.py b/src/bob/learn/em/factor_analysis.py
index d31ba5304f34511d768392f2eb6c4088d9fd9118..e8566204ed44929b1903c6c95776c38c36933142 100644
--- a/src/bob/learn/em/factor_analysis.py
+++ b/src/bob/learn/em/factor_analysis.py
@@ -1632,7 +1632,7 @@ class ISVMachine(FactorAnalysisBase):
             data_sum,
             Ux.reshape((self.ubm.n_gaussians, self.feature_dimension)),
             frame_length_normalization=True,
-        )[0]
+        )[0][0]
 
 
 class JFAMachine(FactorAnalysisBase):
@@ -2293,4 +2293,4 @@ class JFAMachine(FactorAnalysisBase):
             data_sum,
             Ux.reshape((self.ubm.n_gaussians, self.feature_dimension)),
             frame_length_normalization=True,
-        )[0]
+        )[0][0]