Update app.py

app.py

@@ -1,47 +1,46 @@
 import streamlit as st
-import spacy
-
-# Load English language model
-nlp = spacy.load("en_core_web_sm")
-
-def correct_mcq(student_answer, correct_answer):
-    # Process student's answer and correct answer with Spacy
-    doc_student = nlp(student_answer)
-    doc_correct = nlp(correct_answer)
-
-    # Compute similarity between the two answers
-    similarity_score = doc_student.similarity(doc_correct)
-
-    # Provide feedback based on similarity score
-    if similarity_score >= 0.8:
-        feedback = "Correct! Your answer is very similar to the correct answer."
-    elif similarity_score >= 0.6:
-        feedback = "Your answer is close, but there are some differences. Review the correct answer."
-    else:
-        feedback = "Incorrect. Your answer is quite different from the correct answer. Please review."
-
-    return feedback, similarity_score
-
+import logging
+from transformers import pipeline
+
+# Setup logging
+logging.basicConfig(level=logging.INFO)
+
+# Load speech recognition pipeline
+asr = pipeline(task="automatic-speech-recognition",
+               model="facebook/wav2vec2-base-960h")
+
+# Function for transcribing speech
+def transcribe_speech(audio_file):
+    if not audio_file:
+        logging.error("No audio file provided.")
+        return "No audio found, please retry."
+    try:
+        logging.info(f"Processing file: {audio_file.name}")
+        audio_input = audio_file.read()
+        output = asr(audio_input)
+        return output[0]['transcription']
+    except Exception as e:
+        logging.error(f"Error during transcription: {str(e)}")
+        return f"Error processing the audio file: {str(e)}"
+
+# Streamlit app UI
 def main():
-    st.title("Multiple Choice Questions Correction")
-
-    # Text input for student's answer and correct answer
-    student_answer = st.text_area("Student's Answer")
-    correct_answer = st.text_area("Correct Answer")
-
-    if st.button("Check Answer"):
-        if student_answer and correct_answer:
-            # Perform correction
-            feedback, similarity_score = correct_mcq(student_answer, correct_answer)
-
-            # Display feedback and similarity score
-            st.subheader("Feedback")
-            st.write(feedback)
-
-            st.subheader("Similarity Score")
-            st.write(f"{similarity_score:.2f}")
+    st.title("Simple Speech Recognition App")
+    st.write("### This app allows you to record or upload audio and see its transcription.")
+    
+    # Upload audio file or record from microphone
+    audio_file = st.file_uploader("Upload Audio File", type=["wav", "mp3"])
+    if audio_file:
+        st.audio(audio_file, format='audio/wav')
+
+    # Button to transcribe audio
+    if st.button("Transcribe Audio"):
+        if audio_file:
+            transcription = transcribe_speech(audio_file)
+            st.write("### Transcription:")
+            st.write(transcription)
         else:
-            st.warning("Please enter both the student's answer and the correct answer.")
+            st.warning("Please upload an audio file first.")
 
 if __name__ == "__main__":
     main()