Update app.py

app.py

@@ -1,12 +1,63 @@
 import streamlit as st
 from audio_recorder_streamlit import audio_recorder
+import time
+import re
+import os
 
-audio_bytes = audio_recorder()
-print(audio_bytes)
-if audio_bytes:
-    st.audio(audio_bytes, format="audio/wav")
+import whisper
+model = whisper.load_model('medium')
 
-    # To save audio to a file:
-    wav_file = open("audio.mp3", "wb")
-    wav_file.write(audio_bytes)
-    print('Output dump is there')
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+#loading the tokenizer and the model
+tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-hi")
+model_hindi = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-hi")
+
+def translator(text):
+    # function to translate English text to Hindi
+    input_ids = tokenizer.encode(text, return_tensors="pt", padding=True)
+    outputs = model_hindi.generate(input_ids)
+    decoded_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return decoded_text
+
+def split_sentences(generated_text):
+    split_text = re.split(r'(?<!,)[.!?]', generated_text)
+    split_text = [sentence.strip() for sentence in split_text]
+    return split_text
+
+def transcribe(audio):
+    result = model.transcribe(audio)
+    generated_text = result["text"]
+    
+    def process_transcription(generated_text):
+        generated_text = split_sentences(generated_text)
+        processed_text = ""
+
+        for text in generated_text:
+            translated_text = translator(text)
+            processed_text += translated_text + " "
+        
+        return processed_text
+
+    text_hindi = process_transcription(generated_text)
+    return result["text"], text_hindi
+
+def main():
+    st.title("Translate and Transcribe Audio")
+
+    st.write("Click the 'Start Recording' button to start recording your voice. Press 'Stop Recording' when done.")
+    st.write("The transcribed text will be displayed below.")
+
+    audio_bytes = audio_recorder()
+    if audio_bytes:
+        with st.spinner("Transcribing audio... Please wait."):
+            result_text, translated_text = transcribe(audio_bytes)
+
+        st.subheader("Original Text (English):")
+        st.write(result_text)
+
+        st.subheader("Translated Text (Hindi):")
+        st.write(translated_text)
+
+if __name__ == "__main__":
+    main()