Updating Description

app.py

@@ -485,7 +485,7 @@ with gr.Blocks(title="Automatic Literacy and Speech Assesmen") as demo:
                   practice to repeat the same words when it's possible not to. Vocabulary diversity is generally computed by taking the ratio of unique 
                   strings/ total strings. This does not give an indication if the person has a large vocabulary or if the topic does not require a diverse 
                   vocabulary to express it. This algorithm only scores the text based on how many times a unique word was chosen for a semantic idea, e.g., 
-                  "Forest" and "Trees" are 2 words to represent one semantic idea, so this would receive a 100% lexical diversity score, vs using the word
+                  "Forest" and "Woods" are 2 words to represent one semantic idea, so this would receive a 100% lexical diversity score, vs using the word
                   "Forest" twice would yield you a 25% diversity score, (1 unique word/ 2 total words)^2
               """)
   gr.Markdown("""**Speech Pronunciation Scoring-**-  The Wave2Vec 2.0 model is utilized to convert audio into text in real-time. The model predicts words or phonemes