Update app.py

app.py

@@ -11,8 +11,8 @@ synthesiser = pipeline("text-to-speech", "umarigan/speecht5_tts_tr_v1.0")
 embeddings_dataset = load_dataset("umarigan/turkish_voice_dataset_embedded", split="train")
 
 # Define the speech generation function
-def generate_speech(text, speaker_id):
-    speaker_embedding = torch.tensor(embeddings_dataset[speaker_id]["speaker_embeddings"]).unsqueeze(0)
+def generate_speech(text):
+    speaker_embedding = torch.tensor(embeddings_dataset[768]["speaker_embeddings"]).unsqueeze(0)
     speech = synthesiser(text, forward_params={"speaker_embeddings": speaker_embedding})
     
     # Save the generated audio to a file