diff --git a/layers/tacotron.py b/layers/tacotron.py
index fea5af45..2e945844 100644
--- a/layers/tacotron.py
+++ b/layers/tacotron.py
@@ -311,7 +311,7 @@ class Decoder(nn.Module):
                 if t >= T_decoder:
                     break
             else:
-                if t > 1 and stop_token > 0.8:
+                if t > inputs.shape[1]/2 and stop_token > 0.8:
                     break
                 elif t > self.max_decoder_steps:
                     print(" !! Decoder stopped with 'max_decoder_steps'. \
diff --git a/notebooks/utils.py b/notebooks/utils.py
index 47d8f857..b7b7fca6 100644
--- a/notebooks/utils.py
+++ b/notebooks/utils.py
@@ -11,18 +11,9 @@ hop_length = 250
 def create_speech(m, s, CONFIG, use_cuda, ap):
     text_cleaner = [CONFIG.text_cleaner]
     seq = np.array(text_to_sequence(s, text_cleaner))
-
-#     mel = np.zeros([seq.shape[0], CONFIG.num_mels, 1], dtype=np.float32)
-
+    chars_var = torch.from_numpy(seq).unsqueeze(0)
     if use_cuda:
-        chars_var = torch.autograd.Variable(
-            torch.from_numpy(seq), volatile=True).unsqueeze(0).cuda()
-#         mel_var = torch.autograd.Variable(torch.from_numpy(mel).type(torch.cuda.FloatTensor), volatile=True).cuda()
-    else:
-        chars_var = torch.autograd.Variable(
-            torch.from_numpy(seq), volatile=True).unsqueeze(0)
-#         mel_var = torch.autograd.Variable(torch.from_numpy(mel).type(torch.FloatTensor), volatile=True)
-
+        chars_var = chars_var.cuda()
     mel_out, linear_out, alignments, stop_tokens = m.forward(chars_var)
     linear_out = linear_out[0].data.cpu().numpy()
     alignment = alignments[0].cpu().data.numpy()