diff --git a/layers/tacotron2.py b/layers/tacotron2.py
index 48607aea..ecc44a25 100644
--- a/layers/tacotron2.py
+++ b/layers/tacotron2.py
@@ -274,7 +274,6 @@ class Decoder(nn.Module):
         self.attention.init_states(inputs)
 
         outputs, stop_tokens, alignments, t = [], [], [], 0
-        stop_flags = [True, False, False]
         while True:
             memory = self.prenet(memory)
             if speaker_embeddings is not None:
@@ -285,11 +284,7 @@ class Decoder(nn.Module):
             stop_tokens += [stop_token]
             alignments += [alignment]
 
-            stop_flags[0] = stop_flags[0] or stop_token > 0.5
-            stop_flags[1] = stop_flags[1] or (alignment[0, -2:].sum() > 0.8
-                                              and t > inputs.shape[1])
-            stop_flags[2] = t > inputs.shape[1] * 2
-            if all(stop_flags):
+            if stop_token > 0.7:
                 break
             if len(outputs) == self.max_decoder_steps:
                 print("   | > Decoder stopped with 'max_decoder_steps")
@@ -325,11 +320,7 @@ class Decoder(nn.Module):
             stop_tokens += [stop_token]
             alignments += [alignment]
 
-            stop_flags[0] = stop_flags[0] or stop_token > 0.5
-            stop_flags[1] = stop_flags[1] or (alignment[0, -2:].sum() > 0.8
-                                              and t > inputs.shape[1])
-            stop_flags[2] = t > inputs.shape[1] * 2
-            if all(stop_flags):
+            if stop_token > 0.7:
                 break
             if len(outputs) == self.max_decoder_steps:
                 print("   | > Decoder stopped with 'max_decoder_steps")
diff --git a/models/tacotron2.py b/models/tacotron2.py
index c885b8ed..70dd31a5 100644
--- a/models/tacotron2.py
+++ b/models/tacotron2.py
@@ -84,7 +84,7 @@ class Tacotron2(nn.Module):
         encoder_outputs = self.encoder.inference(embedded_inputs)
         encoder_outputs = self._add_speaker_embedding(encoder_outputs,
                                                       speaker_ids)
-        mel_outputs, stop_tokens, alignments = self.decoder.inference(
+        mel_outputs, alignments, stop_tokens = self.decoder.inference(
             encoder_outputs)
         mel_outputs_postnet = self.postnet(mel_outputs)
         mel_outputs_postnet = mel_outputs + mel_outputs_postnet
@@ -100,7 +100,7 @@ class Tacotron2(nn.Module):
         encoder_outputs = self.encoder.inference_truncated(embedded_inputs)
         encoder_outputs = self._add_speaker_embedding(encoder_outputs,
                                                       speaker_ids)
-        mel_outputs, stop_tokens, alignments = self.decoder.inference_truncated(
+        mel_outputs, alignments, stop_tokens = self.decoder.inference_truncated(
             encoder_outputs)
         mel_outputs_postnet = self.postnet(mel_outputs)
         mel_outputs_postnet = mel_outputs + mel_outputs_postnet
diff --git a/utils/synthesis.py b/utils/synthesis.py
index f657eb4d..80d5272f 100644
--- a/utils/synthesis.py
+++ b/utils/synthesis.py
@@ -30,16 +30,12 @@ def compute_style_mel(style_wav, ap, use_cuda):
 
 
 def run_model(model, inputs, CONFIG, truncated, speaker_id=None, style_mel=None):
-    if CONFIG.model == "TacotronGST" and style_mel is not None:
+    if CONFIG.use_gst:
         decoder_output, postnet_output, alignments, stop_tokens = model.inference(
             inputs, style_mel=style_mel, speaker_ids=speaker_id)
     else:
-        if truncated:
-            decoder_output, postnet_output, alignments, stop_tokens = model.inference_truncated(
-                inputs, speaker_ids=speaker_id)
-        else:
-            decoder_output, postnet_output, alignments, stop_tokens = model.inference(
-                inputs, speaker_ids=speaker_id)
+        decoder_output, postnet_output, alignments, stop_tokens = model.inference(
+            inputs, speaker_ids=speaker_id)
     return decoder_output, postnet_output, alignments, stop_tokens