Create app.py

app.py

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+import torch
+from transformers import Speech2TextProcessor, Speech2TextForConditionalGeneration
+from audio_recorder_streamlit import audio_recorder
+import numpy as np
+
+def transcribe_audio(audio_bytes):
+    
+    model = Speech2TextForConditionalGeneration.from_pretrained("facebook/s2t-small-mustc-en-fr-st")
+    processor = Speech2TextProcessor.from_pretrained("facebook/s2t-small-mustc-en-fr-st")
+
+    generated_ids = model.generate(input_ids=audio_bytes["input_features"], attention_mask=audio_bytes["attention_mask"])
+    translation = processor.batch_decode(generated_ids, skip_special_tokens=True)
+
+return translation
+
+
+st.title("Audio to Text Transcription..")
+audio_bytes = audio_recorder(pause_threshold=3.0, sample_rate=16_000)
+if audio_bytes:
+    st.audio(audio_bytes, format="audio/wav")
+
+    transcription = transcribe_audio(audio_bytes)
+    if transcription:
+        st.write("Transcription:")
+        st.write(transcription)
+    else:
+        st.write("Error: Failed to transcribe audio.")
+else:
+    st.write("No audio recorded.")