Update app.py

app.py

@@ -11,16 +11,10 @@ from datasets import load_dataset
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
-def load_models_and_data(language="en"):
+def load_models_and_data():
     model_name = "microsoft/speecht5_tts"
     processor = SpeechT5Processor.from_pretrained(model_name)
-    
-    # Replace with English technical TTS model or regional language-specific model
-    if language == "en":
-        model = SpeechT5ForTextToSpeech.from_pretrained("my_finetuned_english_tech_tts").to(device)
-    else:
-        model = SpeechT5ForTextToSpeech.from_pretrained("my_finetuned_regional_language_tts").to(device)
-    
+    model = SpeechT5ForTextToSpeech.from_pretrained("emirhanbilgic/speecht5_finetuned_emirhan_tr").to(device)
     vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan").to(device)
     
     spk_model_name = "speechbrain/spkrec-xvect-voxceleb"
@@ -31,15 +25,13 @@ def load_models_and_data(language="en"):
     )
     
     # Load a sample from a dataset for default embedding
-    if language == "en":
-        dataset = load_dataset("lj_speech", split="train")
-    else:
-        dataset = load_dataset("regional_language_dataset", split="train")
-    
-    example = dataset[0]
+    dataset = load_dataset("ylacombe/english_dialects ", split="train")
+    example = dataset[304]
     
     return model, processor, vocoder, speaker_model, example
 
+model, processor, vocoder, speaker_model, default_example = load_models_and_data()
+
 # Choose the language dynamically (English or Regional Language)
 model, processor, vocoder, speaker_model, default_example = load_models_and_data(language="en")