diff --git a/autosyl/segment.py b/autosyl/segment.py
index 2f8ac129f6f758c8084d9b402a5c387edb3dea03..5f4d785b7767ce5a92b93f048c3238717e7be823 100644
--- a/autosyl/segment.py
+++ b/autosyl/segment.py
@@ -33,10 +33,16 @@ def segment(songfile, reference_syls=None, syls_per_line=10, last_syl_dur=500):
     #activation_function = np.where(spectral_function > 0.14, cnn_function, 0)
     #onsets = proc(activation_function)
     
+    if reference_syls:
+        activation_threshold = 0.1
+    else:
+        activation_threshold = 0.2
+
+
     activation_smoothed = madmom.audio.signal.smooth(activation_function, 20)
     cnn_smoothed = madmom.audio.signal.smooth(cnn_function, 20)
-    onsets = madmom.features.onsets.peak_picking(activation_smoothed, threshold=0.1, smooth=0)
-    #onsets = np.array([o for o in onsets if cnn_smoothed[o] > 0.1])
+    onsets = madmom.features.onsets.peak_picking(activation_smoothed, threshold=activation_threshold, smooth=0)
+    #onsets = np.array([o for o in onsets if cnn_smoothed[o] > activation_threshold])
 
     pitch = parsel.to_pitch()
     pitch_values = pitch.selected_array['frequency']
@@ -148,8 +154,10 @@ if __name__ == "__main__":
 
 
     songfile = sys.argv[1]
-    if(len(sys.argv) == 3):
+    if(len(sys.argv) >= 3):
         reference_syls = getSyls(sys.argv[2])
+    else:
+        reference_syls = None
     
     #print(reference_syls)
 
@@ -176,9 +184,15 @@ if __name__ == "__main__":
     #activation_function = np.where(spectral_function > 0.14, cnn_function, 0)
     #onsets = proc(activation_function)
     
+
+    if reference_syls:
+        activation_threshold = 0.1
+    else:
+        activation_threshold = 0.2
+
     activation_smoothed = madmom.audio.signal.smooth(activation_function, 20)
     cnn_smoothed = madmom.audio.signal.smooth(cnn_function, 20)
-    onsets = madmom.features.onsets.peak_picking(activation_smoothed, threshold=0.1, smooth=0)
+    onsets = madmom.features.onsets.peak_picking(activation_smoothed, threshold=activation_threshold, smooth=0)
     #onsets = np.array([o for o in onsets if cnn_smoothed[o] > 0.1])
 
     pitch = parsel.to_pitch()
@@ -226,18 +240,20 @@ if __name__ == "__main__":
 
     print(onsets/100)
 
-    reference_onsets = [syl[0]+8 for line in reference_syls for syl in line[:-1]]
+    if reference_syls:
+        reference_onsets = [syl[0]+8 for line in reference_syls for syl in line[:-1]]
 
     fig, axs = plt.subplots(nrows=2, sharex=True)
     axs[0].imshow(log_spec.T, origin='lower', aspect='auto')
-    axs[0].vlines(reference_onsets, 0, 140, colors='red')
+    if reference_syls:
+        axs[0].vlines(reference_onsets, 0, 140, colors='red')
     axs[0].plot((pitch_values/np.max(pitch_values))*140, color='yellow')
     axs[1].plot(mask_function)
     #axs[1].plot(cnn_smoothed)
     #axs[1].plot(spectral_function, color='green')
     axs[1].plot(activation_smoothed, color='orange')
     axs[1].vlines(onsets, 0, 2, colors='red')
-    axs[1].hlines([max(mask_threshold, 0)], 0, onsets[-1]+100, colors='black')
+    axs[1].hlines([max(mask_threshold, 0), activation_threshold], 0, onsets[-1]+100, colors='black')
 
     #bins = np.arange(0, 1, 0.02)
     #hist, hist_axs = plt.subplots(nrows=1)