Update app.py

app.py

@@ -1,11 +1,12 @@
 import os
+import requests
 import speech_recognition as sr
 import difflib
 import gradio as gr
 from gtts import gTTS
-import time
+import io
 from pydub import AudioSegment
-
+import time
 # Create audio directory if it doesn't exist
 if not os.path.exists('audio'):
     os.makedirs('audio')
@@ -48,6 +49,7 @@ def transcribe_audio(audio):
 def create_pronunciation_audio(word):
     time.sleep(5)  # Chờ 5 giây
     tts = gTTS(word)
+    main_url="https://mr2along-speech-recognize.hf.space/gradio_api/file="
     audio_file_path = f"audio/{word}.mp3"  # Save the audio to a file
     tts.save(audio_file_path)
     return audio_file_path  # Return the file path of the saved audio
@@ -62,6 +64,7 @@ def compare_texts(reference_text, transcribed_text):
     similarity_score = round(sm.ratio() * 100, 2)
 
     # Construct HTML output
+   # html_output = f"<strong>Fidelity Class:</strong> # Tạo output HTML với các mức đánh giá chi tiết hơn
     html_output = f"<strong>Fidelity Class:</strong> "
     if similarity_score >= 85:
         html_output += f"<strong>GOOD (>=85%)</strong><br>"
@@ -71,11 +74,12 @@ def compare_texts(reference_text, transcribed_text):
         html_output += f"<strong>NEEDS IMPROVEMENT (50% - 70%)</strong><br>"
     else:
         html_output += f"<strong>POOR (<50%)</strong><br>"
-
+    
     html_output += f"<strong>Quality Score:</strong> {similarity_score}%<br>"
     html_output += f"<strong>Transcribed Text:</strong> {transcribed_text}<br>"
     html_output += "<strong>Word Score List:</strong><br>"
 
+
     # Generate colored word score list
     for i, word in enumerate(reference_words):
         try:
@@ -88,13 +92,16 @@ def compare_texts(reference_text, transcribed_text):
                 html_output += f'<span style="color: red;">{word}</span> '
                 # Create pronunciation audio for the incorrect word
                 audio_file_path = create_pronunciation_audio(word)
-                incorrect_words_audios.append(audio_file_path)
+                #incorrect_words_audios.append((word, audio_file_path))
+                incorrect_words_audios.append( audio_file_path)
         except IndexError:
             html_output += f'<span style="color: red;">{word}</span> '  # Words in reference that were not transcribed
 
     # Provide audio for incorrect words
     if incorrect_words_audios:
         html_output += "<br><strong>Pronunciation for Incorrect Words:</strong><br>"
+
+
     return [html_output, incorrect_words_audios]
 
 # Step 4: Text-to-Speech Function
@@ -111,13 +118,12 @@ def text_to_speech(paragraph):
 def gradio_function(paragraph, audio):
     # Transcribe the audio
     transcribed_text = transcribe_audio(audio)
-
     # Compare the original paragraph with the transcribed text
     comparison_result = compare_texts(paragraph, transcribed_text)
 
     # Return comparison result
     return comparison_result
-
+    
 # Gradio Interface using the updated API
 interface = gr.Interface(
     fn=gradio_function, 
@@ -125,7 +131,7 @@ interface = gr.Interface(
         gr.Textbox(lines=5, label="Input Paragraph"),
         gr.Audio(type="filepath", label="Record Audio")
     ], 
-    outputs=["html", "files"],
+    outputs=["html","files"],
     title="Speech Recognition Comparison",
     description="Input a paragraph, record your audio, and compare the transcription to the original text."
 )
@@ -134,7 +140,7 @@ interface = gr.Interface(
 tts_interface = gr.Interface(
     fn=text_to_speech,
     inputs=gr.Textbox(lines=5, label="Input Paragraph to Read Aloud"),
-    outputs=gr.Microphone(label="Text-to-Speech Output"),
+    outputs=gr.Audio(label="Text-to-Speech Output"),
     title="Text-to-Speech",
     description="This tool will read your input paragraph aloud."
 )
@@ -143,4 +149,4 @@ tts_interface = gr.Interface(
 demo = gr.TabbedInterface([interface, tts_interface], ["Speech Recognition", "Text-to-Speech"])
 
 # Launch Gradio app
-demo.launch()
+demo.launch()