Update app.py

app.py

@@ -1,20 +1,26 @@
-import streamlit as st
-import os
-from scipy.io.wavfile import read
+!pip install torch torchaudio
+!pip install nemo_toolkit[all]
 
-st.title("Voice Cloning Application")
+import torch
+import nemo
+import nemo.collections.asr as nemo_asr
+import nemo.collections.tts as nemo_tts
+from scipy.io.wavfile import write
 
-uploaded_file = st.file_uploader("Upload an audio file", type=["wav"])
-text_input = st.text_input("Enter the text you want to clone")
+# Load pre-trained models
+tacotron2 = nemo_tts.models.Tacotron2Model.from_pretrained("tts_en_tacotron2")
+waveglow = nemo_tts.models.WaveGlowModel.from_pretrained("tts_waveglow_88m")
 
-if uploaded_file is not None and text_input:
-    # Save the uploaded file
-    with open("uploaded_audio.wav", "wb") as f:
-        f.write(uploaded_file.getbuffer())
+def clone_voice(text, audio_path):
+    # Generate spectrogram from text
+    parsed = tacotron2.parse(text)
+    spectrogram = tacotron2.generate_spectrogram(tokens=parsed)
     
-    # Clone the voice
-    clone_voice(text_input, "cloned_voice.wav")
+    # Generate audio from spectrogram
+    audio = waveglow.convert_spectrogram_to_audio(spec=spectrogram)
     
-    # Play the original and cloned audio
-    st.audio("uploaded_audio.wav", format='audio/wav')
-    st.audio("cloned_voice.wav", format='audio/wav')
+    # Save the audio file
+    write(audio_path, 22050, audio.cpu().numpy())
+
+# Example usage
+clone_voice("Hello, this is a cloned voice.", "output.wav")