Amelia-James commited on
Commit
1564098
·
verified ·
1 Parent(s): 0d2a17a

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +18 -16
app.py CHANGED
@@ -14,13 +14,17 @@ st.title("Voice Cloning Application")
14
  st.markdown("Clone your voice using Groq's Whisper Model and generate natural responses.")
15
 
16
  # Upload audio file
17
- uploaded_file = st.file_uploader("Upload your audio file for transcription", type=["wav", "mp3", "m4a"])
 
 
 
18
 
19
  if uploaded_file is not None:
20
- st.audio(uploaded_file, format="audio/wav")
 
21
  st.write("Transcription in progress...")
22
 
23
- # Use Whisper for transcription
24
  try:
25
  transcription = client.chat.completions.create(
26
  messages=[
@@ -37,22 +41,20 @@ if uploaded_file is not None:
37
  st.success("Transcription completed!")
38
  st.write("**Transcribed Text:**", transcribed_text)
39
 
40
- # Add voice cloning logic here (future step)
 
 
 
 
 
 
 
 
 
 
41
 
42
  except Exception as e:
43
  st.error(f"Error during transcription: {e}")
44
 
45
- # Text-to-Speech (Optional)
46
- st.markdown("---")
47
- st.subheader("Generate Speech from Transcription")
48
- tts_input = st.text_area("Enter text to generate speech:")
49
-
50
- if st.button("Generate Speech"):
51
- if tts_input:
52
- # Simulate TTS functionality (add actual TTS model later)
53
- st.success("Generated speech successfully! (Placeholder)")
54
- else:
55
- st.warning("Please enter some text.")
56
-
57
  # Footer
58
  st.markdown("Developed with ❤️ by Sanam Iftakhar")
 
14
  st.markdown("Clone your voice using Groq's Whisper Model and generate natural responses.")
15
 
16
  # Upload audio file
17
+ uploaded_file = st.file_uploader(
18
+ "Upload your audio file for transcription",
19
+ type=["wav", "mp3", "mp4", "m4a"]
20
+ )
21
 
22
  if uploaded_file is not None:
23
+ # Display uploaded audio
24
+ st.audio(uploaded_file, format=f"audio/{uploaded_file.type.split('.')[-1]}")
25
  st.write("Transcription in progress...")
26
 
27
+ # Transcription Logic
28
  try:
29
  transcription = client.chat.completions.create(
30
  messages=[
 
41
  st.success("Transcription completed!")
42
  st.write("**Transcribed Text:**", transcribed_text)
43
 
44
+ # Placeholder for voice cloning (TTS integration can go here)
45
+ st.markdown("---")
46
+ st.subheader("Generate Speech from Transcription")
47
+ tts_input = st.text_area("Enter text to generate speech:", value=transcribed_text)
48
+
49
+ if st.button("Generate Speech"):
50
+ if tts_input:
51
+ # Simulate TTS functionality (placeholder for TTS model integration)
52
+ st.success("Generated speech successfully! (Placeholder)")
53
+ else:
54
+ st.warning("Please enter some text.")
55
 
56
  except Exception as e:
57
  st.error(f"Error during transcription: {e}")
58
 
 
 
 
 
 
 
 
 
 
 
 
 
59
  # Footer
60
  st.markdown("Developed with ❤️ by Sanam Iftakhar")