Update app.py

app.py

@@ -4,6 +4,7 @@ from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
 from transformers import MarianMTModel, MarianTokenizer
 import soundfile as sf
 from datasets import load_dataset
+import os
 
 # Device setup
 device = "cuda:0" if torch.cuda.is_available() else "cpu"
@@ -82,7 +83,12 @@ if st.button("Listen to Translated Audio"):
         speech = tts_pipe(st.session_state.translated_text, forward_params={"speaker_embeddings": speaker_embedding})
         st.session_state.audio_path = "translated_speech.wav"
         sf.write(st.session_state.audio_path, speech["audio"], samplerate=speech["sampling_rate"])
-        st.audio(st.session_state.audio_path, format="audio/wav")
+        
+        # Ensure the audio file exists and display the player
+        if os.path.exists(st.session_state.audio_path):
+            st.audio(st.session_state.audio_path, format="audio/wav")
+        else:
+            st.error("Failed to generate audio. Please try again.")
     else:
         st.error("Please submit the text first.")
 
@@ -98,4 +104,4 @@ if st.button("Reset"):
 if st.session_state.translated_text and not st.session_state.audio_path:
     st.write(f"Translated text: {st.session_state.translated_text}")
 elif st.session_state.audio_path:
-    st.audio(st.session_state.audio_path, format="audio/wav")
+    st.audio(st.session_state.audio_path, format="audio/wav")