Add the language embedding dim in the duration predictor class

TTS/tts/layers/glow_tts/duration_predictor.py

@@ -20,6 +20,11 @@ class DurationPredictor(nn.Module):
 
     def __init__(self, in_channels, hidden_channels, kernel_size, dropout_p, cond_channels=None, language_emb_dim=None):
         super().__init__()
+
+        # add language embedding dim in the input
+        if language_emb_dim:
+            in_channels += language_emb_dim
+
         # class arguments
         self.in_channels = in_channels
         self.filter_channels = hidden_channels

TTS/tts/layers/vits/stochastic_duration_predictor.py

@@ -185,10 +185,14 @@ class StochasticDurationPredictor(nn.Module):
         dropout_p: float,
         num_flows=4,
         cond_channels=0,
-        language_emb_dim=None,
+        language_emb_dim=0,
     ):
         super().__init__()
 
+        # add language embedding dim in the input
+        if language_emb_dim:
+            in_channels += language_emb_dim
+
         # condition encoder text
         self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
         self.convs = DilatedDepthSeparableConv(hidden_channels, kernel_size, num_layers=3, dropout_p=dropout_p)

TTS/tts/models/vits.py

@@ -321,7 +321,7 @@ class Vits(BaseTTS):
 
         if args.use_sdp:
             self.duration_predictor = StochasticDurationPredictor(
-                args.hidden_channels + self.embedded_language_dim,
+                args.hidden_channels,
                 192,
                 3,
                 args.dropout_p_duration_predictor,
@@ -331,7 +331,7 @@ class Vits(BaseTTS):
             )
         else:
             self.duration_predictor = DurationPredictor(
-                args.hidden_channels + self.embedded_language_dim,
+                args.hidden_channels,
                 256,
                 3,
                 args.dropout_p_duration_predictor,