diff --git a/parakeet/models/tacotron2.py b/parakeet/models/tacotron2.py
index f7efd58..59699d9 100644
--- a/parakeet/models/tacotron2.py
+++ b/parakeet/models/tacotron2.py
@@ -607,7 +607,7 @@ class Tacotron2(nn.Layer):
                                       num_layers=postnet_conv_layers,
                                       dropout=p_postnet_dropout)
 
-    def forward(self, text_inputs, text_lens, mels, output_lens=None, speaker_ids=None, tones=None):
+    def forward(self, text_inputs, text_lens, mels, output_lens=None, speaker_ids=None, tones=None, global_condition=None):
         """Calculate forward propagation of tacotron2.
 
         Parameters
@@ -645,6 +645,8 @@ class Tacotron2(nn.Layer):
             speaker_embedding = self.speaker_embedding(speaker_ids)
             speaker_feature = F.softplus(self.speaker_fc(speaker_embedding))
             encoder_outputs += speaker_feature.unsqueeze(1)
+        if global_condition is not None:
+            encoder_outputs += global_condition.unsqueeze(1)
             
 
         # [B, T_enc, 1]
@@ -671,7 +673,7 @@ class Tacotron2(nn.Layer):
         return outputs
 
     @paddle.no_grad()
-    def infer(self, text_inputs, max_decoder_steps=1000, speaker_ids=None, tones=None):
+    def infer(self, text_inputs, max_decoder_steps=1000, speaker_ids=None, tones=None, global_condition=None):
         """Generate the mel sepctrogram of features given the sequences of character ids.
 
         Parameters
@@ -702,6 +704,8 @@ class Tacotron2(nn.Layer):
             speaker_embedding = self.speaker_embedding(speaker_ids)
             speaker_feature = F.softplus(self.speaker_fc(speaker_embedding))
             encoder_outputs += speaker_feature.unsqueeze(1)
+        if global_condition is not None:
+            encoder_outputs += global_condition.unsqueeze(1)        
             
         mel_outputs, alignments = self.decoder.infer(
             encoder_outputs, max_decoder_steps=max_decoder_steps)