Update app.py

app.py

@@ -1,7 +1,5 @@
 import streamlit as st
 from transformers import pipeline
-import torch
-from scipy.io.wavfile import write
 import numpy as np
 
 # Load Hugging Face pipelines
@@ -32,15 +30,19 @@ if st.button("Analyze Comment"):
         feedback = feedback_generator(f"emotion: {emotion_label} text: {comment_input}", max_length=50)[0]["generated_text"]
 
         # Convert feedback text to speech
-        audio_output = text_to_audio(feedback)
-        audio_array = np.array(audio_output["audio"]) * 32767  # Convert to int16 range
-        audio_path = "feedback_audio.wav"
-        write(audio_path, 22050, audio_array.astype(np.int16))
+        st.text('Generating audio data...')
+        audio_data = text_to_audio(feedback)
+        
         
         # Display results
         st.subheader("Analysis Result")
         st.write(f"### **Emotion:** {emotion_label} (Confidence: {emotion_score})")
         st.write(f"### **Generated Feedback:** {feedback}")
         
-        # Audio output
-        st.audio(audio_path, format="audio/wav")
+
+        # Play button
+        if st.button("Play Audio"):
+           st.audio(audio_data['audio'],
+                    format="audio/wav",
+                    start_time=0,
+                    sample_rate = audio_data['sampling_rate'])