Update app.py

app.py

@@ -0,0 +1,32 @@
+import torch
+import torchaudio
+from transformers import pipeline
+import streamlit as st
+
+# Load the pre-trained wav2vec 2.0 model
+model = pipeline('voice-recognition', model='facebook/wav2vec2-base-960h')
+
+def recognize_voice(audio_file):
+    waveform, sample_rate = torchaudio.load(audio_file)
+    transcript = model(waveform.numpy()[0], sample_rate=sample_rate)
+    return transcript[0]['sentence']
+
+def main():
+    st.title("Voice Recognition App")
+
+    # Upload audio file
+    audio_file = st.file_uploader("Upload an audio file", type=["mp3", "wav"])
+
+    if audio_file is not None:
+        st.audio(audio_file, format='audio/wav')
+
+        if st.button("Recognize Voice"):
+            try:
+                # Perform voice recognition
+                result = recognize_voice(audio_file)
+                st.success(f"Recognition Result: {result}")
+            except Exception as e:
+                st.error(f"Error: {e}")
+
+if __name__ == "__main__":
+    main()