Update app.py

app.py

@@ -1,11 +1,18 @@
 import streamlit as st
 import whisper
+from sklearn.feature_extraction.text import TfidfVectorizer
+from sklearn.metrics.pairwise import cosine_similarity
 
+def cosine_sim(text1, text2):
+    vectorizer = TfidfVectorizer().fit_transform([text1, text2])
+    vectors = vectorizer.toarray()
+    return cosine_similarity(vectors)[0, 1]
+    
 model = whisper.load_model("base")
 st.audio("titanic.mp3")
-st.write("Please wait for the music to finish before recording the rest of it by your own.")
+st.write("Listen to music since you have to record 15seconds after that")
 
-audio_value = st.experimental_audio_input("Record a voice message")
+audio_value = st.experimental_audio_input("Sing Rest of music:🎙️")
 lyrics = "Far across the distance And spaces between us You have come to show you go on"
 
 if audio_value:
@@ -14,4 +21,6 @@ if audio_value:
 
     user_lyrics = model.transcribe("user_sing.mp3")["text"]
     st.write(user_lyrics)
-    
+    similarity_score = cosine_sim(lyrics, user_lyrics)
+    if similarity_score > 0.85:
+        st.success('This is a success message!', icon="✅")