Update app.py

app.py

@@ -22,19 +22,12 @@ speaker_embeddings = torch.tensor(embeddings_dataset[7440]["xvector"]).unsqueeze
 processor = SpeechT5Processor.from_pretrained(model_id)
 
 replacements = [
-     ("á", "a"),
-     ("ç", "c"),
-     ("è", "e"),
-     ("ì", "i"),
-     ("í", "i"),
-     ("ò", "o"),
-     ("ó", "o"),
-     ("ù", "u"),
-     ("ú", "u"),
-     ("š", "s"),
-     ("ï", "i"),
-     ("ñ", "n"),
-     ("ü", "u"),
+    ("à", "a"), ("â", "a"),
+    ("ç", "c"),
+    ("é", "e"), ("è", "e"), ("ê", "e"), ("ë", "e"),
+    ("î", "i"), ("ï", "i"),
+    ("ô", "o"),
+    ("ù", "u"), ("û", "u"),
 ]
 
 def cleanup_text(text):