diff --git a/app.py b/app.py
index 3dbebf0..3649491 100644
--- a/app.py
+++ b/app.py
@@ -6,7 +6,7 @@ from firebase_admin import credentials
 from helper.api_messages import QuestionType, get_grading_messages, get_question_gen_messages, get_question_tips
 from helper.file_helper import delete_files_older_than_one_day
 from helper.firebase_helper import download_firebase_file, upload_file_firebase
-from helper.speech_to_text_helper import speech_to_text, text_to_speech
+from helper.speech_to_text_helper import speech_to_text, text_to_speech, has_words
 from helper.token_counter import count_tokens
 from helper.openai_interface import make_openai_call
 import os
@@ -200,16 +200,18 @@ def grade_speaking_task_1():
 
         download_firebase_file(FIREBASE_BUCKET, answer_firebase_path, sound_file_name)
         answer = speech_to_text(sound_file_name)
-
-        messages = get_grading_messages(QuestionType.SPEAKING_1, question, answer)
-        token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
-                             map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
-        response = make_openai_call(GPT_3_5_TURBO, messages, token_count, GRADING_FIELDS, GRADING_TEMPERATURE)
-        os.remove(sound_file_name)
-        return response
+        if has_words(answer):
+            messages = get_grading_messages(QuestionType.SPEAKING_1, question, answer)
+            token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
+                                 map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
+            response = make_openai_call(GPT_3_5_TURBO, messages, token_count, GRADING_FIELDS, GRADING_TEMPERATURE)
+            os.remove(sound_file_name)
+            return response
+        else:
+            raise Exception("The audio recorded does not contain any english words.")
     except Exception as e:
         os.remove(sound_file_name)
-        return str(e)
+        return str(e), 400
 
 
 @app.route('/speaking_task_1', methods=['GET'])
@@ -237,16 +239,18 @@ def grade_speaking_task_2():
 
         download_firebase_file(FIREBASE_BUCKET, answer_firebase_path, sound_file_name)
         answer = speech_to_text(sound_file_name)
-
-        messages = get_grading_messages(QuestionType.SPEAKING_2, question, answer)
-        token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
-                             map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
-        response = make_openai_call(GPT_3_5_TURBO, messages, token_count, GRADING_FIELDS, GRADING_TEMPERATURE)
-        os.remove(sound_file_name)
-        return response
+        if has_words(answer):
+            messages = get_grading_messages(QuestionType.SPEAKING_2, question, answer)
+            token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
+                                 map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
+            response = make_openai_call(GPT_3_5_TURBO, messages, token_count, GRADING_FIELDS, GRADING_TEMPERATURE)
+            os.remove(sound_file_name)
+            return response
+        else:
+            raise Exception("The audio recorded does not contain any english words.")
     except Exception as e:
         os.remove(sound_file_name)
-        return str(e)
+        return str(e), 400
 
 
 @app.route('/speaking_task_2', methods=['GET'])
diff --git a/helper/speech_to_text_helper.py b/helper/speech_to_text_helper.py
index 4f63123..76669bb 100644
--- a/helper/speech_to_text_helper.py
+++ b/helper/speech_to_text_helper.py
@@ -1,7 +1,9 @@
 import whisper
 import os
 import gtts
-from playsound import playsound
+import nltk
+nltk.download('words')
+from nltk.corpus import words
 
 def speech_to_text(file_path):
     if os.path.exists(file_path):
@@ -14,4 +16,9 @@ def speech_to_text(file_path):
 
 def text_to_speech(text: str, file_name: str):
     tts = gtts.gTTS(text)
-    tts.save(file_name)
\ No newline at end of file
+    tts.save(file_name)
+
+def has_words(text: str):
+    english_words = set(words.words())
+    words_in_input = text.split()
+    return any(word.lower() in english_words for word in words_in_input)
\ No newline at end of file