info in sstream

sstream.py

@@ -287,7 +287,6 @@ class SStream(object):
 
             # Apply pre-emphasis filtering if required
             sliding_sig = sliding_sig - np.c_[sliding_sig[..., :1], sliding_sig[..., :-1]] * self.prefac
-
             # Compute logEnergy and send it as first coefficient
             if self.log_energy:
                 energy = np.log((sliding_sig**2).sum(axis=1))
@@ -318,7 +317,6 @@ class SStream(object):
                                                    nwin=self._win_size)
             # Apply smoothing on the labels
             vad = sidekit.frontend.vad.label_fusion(vad)
-
             while idx < sliding_sig.shape[0]:
                 next_routine.send((sliding_sig[idx:idx+self.buffer_size, :].squeeze(), energy, vad))
                 idx += self.buffer_size
@@ -336,7 +334,7 @@ class SStream(object):
             while True:
                 sig = yield
                 if sig.squeeze().ndim == 1:
-                    assert second_channel is None, "Error: too many followers"
+                    assert second_channel is None, "Error: too many followers in {}".format(self.input_filename)
                     first_channel.send(sig.squeeze())
                 elif sig.squeeze().shape[1] == 2:
                     assert second_channel is not None, "Error: missing second follower"