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| # app.py | |
| import gradio as gr | |
| import speech_recognition as sr | |
| from Levenshtein import ratio | |
| import tempfile | |
| import numpy as np | |
| import soundfile as sf | |
| def transcribe_audio(file_info): | |
| r = sr.Recognizer() | |
| with tempfile.NamedTemporaryFile(delete=True, suffix=".wav") as tmpfile: | |
| sf.write(tmpfile.name, data=file_info, samplerate=44100, format='WAV') | |
| tmpfile.seek(0) | |
| with sr.AudioFile(tmpfile.name) as source: | |
| audio_data = r.record(source) | |
| try: | |
| text = r.recognize_google(audio_data) | |
| return text | |
| except sr.UnknownValueError: | |
| return "Could not understand audio" | |
| except sr.RequestError as e: | |
| return f"Could not request results; {e}" | |
| def pronunciation_correction(expected_text, file_info): | |
| user_spoken_text = transcribe_audio(file_info) | |
| similarity = ratio(expected_text.lower(), user_spoken_text.lower()) | |
| description = f"{similarity:.2f}" | |
| if similarity >= 0.9: | |
| feedback = "Excellent pronunciation!" | |
| elif similarity >= 0.7: | |
| feedback = "Good pronunciation!" | |
| elif similarity >= 0.5: | |
| feedback = "Needs improvement." | |
| else: | |
| feedback = "Poor pronunciation, try to focus more on clarity." | |
| return feedback, description | |
| def grammar_check(sentence): | |
| # Example implementation of a grammar checker function | |
| # Ideally, you would use a grammar checking API or tool | |
| # This is a placeholder to show the structure | |
| if not sentence.endswith("."): | |
| return "Sentence should end with a period." | |
| if len(sentence.split()) < 3: | |
| return "Sentence is too short. Please provide more details." | |
| return "No grammar issues found." | |
| with gr.Blocks() as app: | |
| with gr.Column(): | |
| text_input = gr.Textbox(label="Type your sentence here", lines=5, placeholder="Type here...") | |
| grammar_check_button = gr.Button("Check Grammar") | |
| grammar_feedback = gr.Textbox(label="Grammar Feedback", interactive=False) | |
| audio_input = gr.Audio(label="Upload Audio File", type="numpy") | |
| check_pronunciation_button = gr.Button("Check Pronunciation") | |
| pronunciation_feedback = gr.Textbox(label="Pronunciation Feedback") | |
| pronunciation_score = gr.Number(label="Pronunciation Accuracy Score: 0 (No Match) ~ 1 (Perfect)") | |
| grammar_check_button.click( | |
| grammar_check, | |
| inputs=text_input, | |
| outputs=grammar_feedback | |
| ) | |
| check_pronunciation_button.click( | |
| pronunciation_correction, | |
| inputs=[text_input, audio_input], | |
| outputs=[pronunciation_feedback, pronunciation_score] | |
| ) | |
| app.launch(debug=True) | |
| # app.py | |
| import gradio as gr | |
| import speech_recognition as sr | |
| from Levenshtein import ratio | |
| import tempfile | |
| import numpy as np | |
| import soundfile as sf | |
| def transcribe_audio(file_info): | |
| r = sr.Recognizer() | |
| with tempfile.NamedTemporaryFile(delete=True, suffix=".wav") as tmpfile: | |
| sf.write(tmpfile.name, data=file_info, samplerate=44100, format='WAV') | |
| tmpfile.seek(0) | |
| with sr.AudioFile(tmpfile.name) as source: | |
| audio_data = r.record(source) | |
| try: | |
| text = r.recognize_google(audio_data) | |
| return text | |
| except sr.UnknownValueError: | |
| return "Could not understand audio" | |
| except sr.RequestError as e: | |
| return f"Could not request results; {e}" | |
| def pronunciation_correction(expected_text, file_info): | |
| user_spoken_text = transcribe_audio(file_info) | |
| similarity = ratio(expected_text.lower(), user_spoken_text.lower()) | |
| description = f"{similarity:.2f}" | |
| if similarity >= 0.9: | |
| feedback = "Excellent pronunciation!" | |
| elif similarity >= 0.7: | |
| feedback = "Good pronunciation!" | |
| elif similarity >= 0.5: | |
| feedback = "Needs improvement." | |
| else: | |
| feedback = "Poor pronunciation, try to focus more on clarity." | |
| return feedback, description | |
| def grammar_check(sentence): | |
| # Example implementation of a grammar checker function | |
| # Ideally, you would use a grammar checking API or tool | |
| # This is a placeholder to show the structure | |
| if not sentence.endswith("."): | |
| return "Sentence should end with a period." | |
| if len(sentence.split()) < 3: | |
| return "Sentence is too short. Please provide more details." | |
| return "No grammar issues found." | |
| with gr.Blocks() as app: | |
| with gr.Column(): | |
| text_input = gr.Textbox(label="Type your sentence here", lines=5, placeholder="Type here...") | |
| grammar_check_button = gr.Button("Check Grammar") | |
| grammar_feedback = gr.Textbox(label="Grammar Feedback", interactive=False) | |
| audio_input = gr.Audio(label="Upload Audio File", type="numpy") | |
| check_pronunciation_button = gr.Button("Check Pronunciation") | |
| pronunciation_feedback = gr.Textbox(label="Pronunciation Feedback") | |
| pronunciation_score = gr.Number(label="Pronunciation Accuracy Score: 0 (No Match) ~ 1 (Perfect)") | |
| grammar_check_button.click( | |
| grammar_check, | |
| inputs=text_input, | |
| outputs=grammar_feedback | |
| ) | |
| check_pronunciation_button.click( | |
| pronunciation_correction, | |
| inputs=[text_input, audio_input], | |
| outputs=[pronunciation_feedback, pronunciation_score] | |
| ) | |
| app.launch(debug=True) | |