Update app.py

app.py

@@ -10,7 +10,7 @@ def transcribe_audio(audio):
 
     # Convert audio into recognizable format for the Recognizer
     audio_file = sr.AudioFile(audio)
-    
+
     with audio_file as source:
         audio_data = recognizer.record(source)
 
@@ -25,7 +25,7 @@ def transcribe_audio(audio):
 
 # Step 2: Create pronunciation audio for incorrect words
 def create_pronunciation_audio(word):
-    tts = gTTS(word)
+    tts = gTTS(word, lang='en')  # Specify the language for TTS
     audio_buffer = io.BytesIO()
     tts.save(audio_buffer)
     audio_buffer.seek(0)
@@ -49,7 +49,7 @@ def compare_texts(reference_text, transcribed_text):
 
     # Generate colored word score list
     for i, word in enumerate(reference_words):
-        try:
+        if i < len(transcribed_words):
             if word.lower() == transcribed_words[i].lower():
                 html_output += f'<span style="color: green;">{word}</span> '  # Correct words in green
             elif difflib.get_close_matches(word, transcribed_words):
@@ -62,7 +62,8 @@ def compare_texts(reference_text, transcribed_text):
                 # Encode the audio as base64 for playback
                 audio_base64 = audio_buffer.getvalue().hex()
                 incorrect_words_audios.append((word, audio_base64))
-        except IndexError:
+        else:
+            # If reference word has no corresponding transcribed word
             html_output += f'<span style="color: red;">{word}</span> '  # Words in reference that were not transcribed
 
     # Provide audio for incorrect words
@@ -77,7 +78,7 @@ def compare_texts(reference_text, transcribed_text):
 
 # Step 4: Text-to-Speech Function
 def text_to_speech(paragraph):
-    tts = gTTS(paragraph)
+    tts = gTTS(paragraph, lang='en')  # Specify the language for TTS
     audio_buffer = io.BytesIO()
     tts.save(audio_buffer)
     audio_buffer.seek(0)