Update app.py

app.py

@@ -0,0 +1,34 @@
+
+import streamlit as st
+from transformers import pipeline
+import scipy.io.wavfile
+import numpy as np
+import os
+
+# Load the text-to-speech pipeline
+synthesizer = pipeline("text-to-speech", model="suno/bark")
+
+# Streamlit app
+st.title("Text-to-Speech with Suno/Bark Model")
+
+# Text input from the user
+text = st.text_area("Enter the text you want to convert to speech:", "")
+
+if st.button("Generate Speech"):
+    if text:
+        with st.spinner("Generating speech..."):
+            # Generate speech from text
+            speech = synthesizer(text, forward_params={"do_sample": True})
+            
+            # Save the speech as a WAV file
+            output_path = "output.wav"
+            scipy.io.wavfile.write(output_path, rate=speech["sampling_rate"], data=np.array(speech["audio"]))
+            
+            st.success("Speech generated successfully!")
+            
+            # Provide options to play and download the audio file
+            audio_file = open(output_path, "rb").read()
+            st.audio(audio_file, format="audio/wav")
+            st.download_button(label="Download WAV file", data=audio_file, file_name="output.wav", mime="audio/wav")
+    else:
+        st.error("Please enter some text to generate speech.")