add mozilla german

datasets/preprocess.py

@@ -60,22 +60,6 @@ def tweb(root_path, meta_file):
 #     return  {'text': texts, 'wavs': wavs}
 
 
-def mozilla_old(root_path, meta_file):
-    """Normalizes Mozilla meta data files to TTS format"""
-    txt_file = os.path.join(root_path, meta_file)
-    items = []
-    speaker_name = "mozilla_old"
-    with open(txt_file, 'r') as ttf:
-        for line in ttf:
-            cols = line.split('|')
-            batch_no = int(cols[1].strip().split("_")[0])
-            wav_folder = "batch{}".format(batch_no)
-            wav_file = os.path.join(root_path, wav_folder, "wavs_no_processing", cols[1].strip())
-            text = cols[0].strip()
-            items.append([text, wav_file, speaker_name])
-    return items
-
-
 def mozilla(root_path, meta_file):
     """Normalizes Mozilla meta data files to TTS format"""
     txt_file = os.path.join(root_path, meta_file)
@@ -91,6 +75,22 @@ def mozilla(root_path, meta_file):
     return items
 
 
+def mozilla_de(root_path, meta_file):
+    """Normalizes Mozilla meta data files to TTS format"""
+    txt_file = os.path.join(root_path, meta_file)
+    items = []
+    speaker_name = "mozilla"
+    with open(txt_file, 'r', encoding="ISO 8859-1") as ttf:
+        for line in ttf:
+            cols = line.strip().split('|')
+            wav_file = cols[0].strip()
+            text = cols[1].strip()            
+            folder_name = f"BATCH_{wav_file.split('_')[0]}_FINAL"
+            wav_file = os.path.join(root_path, folder_name, wav_file)
+            items.append([text, wav_file, speaker_name])
+    return items
+
+
 def mailabs(root_path, meta_files=None):
     """Normalizes M-AI-Labs meta data files to TTS format"""
     speaker_regex = re.compile("by_book/(male|female)/(?P<speaker_name>[^/]+)/")

layers/tacotron2.py

@@ -64,7 +64,6 @@ class Encoder(nn.Module):
     def forward(self, x, input_lengths):
         x = self.convolutions(x)
         x = x.transpose(1, 2)
-        input_lengths = input_lengths.cpu().numpy()
         x = nn.utils.rnn.pack_padded_sequence(x,
                                               input_lengths,
                                               batch_first=True)