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| # Module Imports | |
| from pytube import YouTube | |
| import whisper | |
| import gradio as gr | |
| import time | |
| import re | |
| from happytransformer import HappyTextToText, TTSettings | |
| from difflib import Differ | |
| STTmodel = whisper.load_model("base.en") | |
| GCmodel = HappyTextToText("T5", "Ragnov/T5-Base-Grammar-Checker") | |
| args = TTSettings(num_beams=5, min_length=1) | |
| # Functions | |
| def transcribe(file): | |
| options = dict(task="transcribe", best_of=5) | |
| text = STTmodel.transcribe(file, **options)["text"] | |
| return text.strip() | |
| def get_filename(file_obj): | |
| return file_obj.orig_name | |
| def inference(link): | |
| yt = YouTube(link) | |
| path = yt.streams.filter(only_audio=True)[0].download(filename="audio.mp4") | |
| options = whisper.DecodingOptions(without_timestamps=True) | |
| results = STTmodel.transcribe(path) | |
| return results['text'] | |
| def populate_metadata(link): | |
| yt = YouTube(link) | |
| return yt.thumbnail_url, yt.title | |
| def transcribe_file(file): | |
| options = dict(task="transcribe", best_of=5) | |
| file = get_filename(file) | |
| text = STTmodel.transcribe(file, **options)["text"] | |
| return text.strip() | |
| def real_time_transcribe(audio, state=""): | |
| time.sleep(2) | |
| text = STTmodel.transcribe(audio)["text"] | |
| state += text + " " | |
| return state, state | |
| def paragraph_to_sentences(paragraph): | |
| """ | |
| This function takes a paragraph as input and returns a list of sentences. | |
| Args: | |
| paragraph (str): The paragraph to be converted to a list of sentences. | |
| Returns: | |
| list: A list of sentences extracted from the paragraph. | |
| """ | |
| # Split the paragraph into sentences using a period, exclamation mark or question mark as the delimiter. | |
| sentences = re.split(r'(?<=[^A-Z].[.?!]) +(?=[A-Z])|(?<=[^A-Z][!]) +(?=[A-Z])', paragraph) | |
| # Remove any leading or trailing spaces from each sentence. | |
| sentences = [sentence.strip() for sentence in sentences] | |
| return sentences | |
| def sentences_to_paragraph(sentences): | |
| final_result = "" | |
| for num, sentence in enumerate(sentences): | |
| result = GCmodel.generate_text("grammar: "+ sentence, args=args) | |
| final_result += result.text | |
| if num < len(sentences) - 1: | |
| final_result += " " | |
| return final_result | |
| # Function that takes transcribed result and gramify it | |
| def gramify(paragraph): | |
| result_1 = paragraph_to_sentences(paragraph) | |
| final_result = sentences_to_paragraph(result_1) | |
| return final_result | |
| # Function that takes transcribed text for its first inpu | |
| def diff_texts(text1, text2): | |
| """ | |
| This function takes transcribed text for its first input | |
| and grammatically corrected text as its second input which return the difference | |
| of the two text. | |
| """ | |
| d = Differ() | |
| return [ | |
| (token[2:], token[0] if token[0] != " " else None) | |
| for token in d.compare(text1, text2) | |
| ] | |
| res_diff = [] | |
| # Gradio Blocks | |
| demo = gr.Blocks() | |
| with demo: | |
| gr.Markdown(""" <p style="text-align: center;"> Speech To Text Grammar Checker </p>""") | |
| with gr.Tabs(): | |
| with gr.TabItem("Voice Record"): | |
| with gr.Row(): | |
| audio = gr.Audio(show_label=False,source="microphone",type="filepath") | |
| text_output1 = gr.Textbox(label="Transcription", placeholder="Text Output") | |
| with gr.Row(): | |
| transcribe_button1 = gr.Button("Transcribe") | |
| with gr.Row(): | |
| Grammar_text_output1 = gr.Textbox(label="Grammatically Corrected Text", placeholder="Text Output") | |
| with gr.Row(): | |
| Diff_text_output1 = gr.HighlightedText(label="Text Difference",combine_adjacent=True,value=res_diff).style(color_map={"+": "green", "-": "red"}) | |
| with gr.TabItem("Upload File"): | |
| with gr.Row(): | |
| file_upload = gr.File() | |
| text_output2 = gr.Textbox(label="Transcription", placeholder="Text Output") | |
| with gr.Row(): | |
| transcribe_button2 = gr.Button("Transcribe") | |
| with gr.Row(): | |
| Grammar_text_output2 = gr.Textbox(label="Grammatically Corrected Text", placeholder="Text Output") | |
| with gr.Row(): | |
| Diff_text_output2 = gr.HighlightedText(label="Text Difference",combine_adjacent=True,value=res_diff).style(color_map={"+": "green", "-": "red"}) | |
| with gr.TabItem("Youtube Link"): | |
| with gr.Box(): | |
| link = gr.Textbox(label="YouTube Link") | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| title = gr.Label(label="Video Title", placeholder="Title") | |
| img = gr.Image(label="Thumbnail") | |
| text_link_output = gr.Textbox(label="Transcription", placeholder="Text Output",lines=5) | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| transcribe_button3 = gr.Button("Transcribe") | |
| with gr.Row(): | |
| Grammar_text_output3 = gr.Textbox(label="Grammatically Corrected Text", placeholder="Text Output") | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| Diff_text_output3 = gr.HighlightedText(label="Text Difference",combine_adjacent=True,value=res_diff).style(color_map={"+": "green", "-": "red"}) | |
| gr.Markdown("""<p style="text-align: center;"> Not Satisfied with the result? </br> | |
| <a href="https://forms.gle/yZA5DBygMUNmLZtv7">Click here to help us make it better.</a> | |
| </p>""") | |
| with gr.Accordion("About",open=False): | |
| gr.Markdown(""" | |
| <p style="text-align: center;"> Thesis System presented by <br/> <br/> | |
| • <b>Daniel L. Espinola</b> <br/> | |
| • <b>Jhon Vincent A. Gupo</b> <br/> | |
| • <b>Ryan M. Ibay</b> <br/> <br/> | |
| In partial fulfillment of the requirements for the degree <br/> | |
| Bachelor of Science in Computer Science Specialized in Intelligent Systems <br/> | |
| Laguna State Polytechnic University - Los Baños Campus . <br/> <br/> | |
| We would also like to thank our fellow adviser and subject specialist for their guidance in making this idea a reality. <br/> | |
| • <b>Crisanto F. Gulay</b> - Adviser <br/> | |
| • <b>Gene Marck B. Catedrilla</b> - Subject Specialist <br/> | |
| </p> | |
| """) | |
| link.change(populate_metadata, inputs=[link], outputs=[img, title]) | |
| # Transcription | |
| transcribe_button1.click(transcribe, inputs=audio, outputs=text_output1) | |
| transcribe_button2.click(transcribe_file, inputs=file_upload, outputs=text_output2) | |
| transcribe_button3.click(inference, inputs=link, outputs=text_link_output) | |
| # Gramify | |
| text_output1.change(gramify,inputs=text_output1,outputs=Grammar_text_output1) | |
| text_output2.change(gramify,inputs=text_output2,outputs=Grammar_text_output2) | |
| text_link_output.change(gramify, inputs=text_link_output ,outputs=Grammar_text_output3) | |
| # For Text Difference | |
| Grammar_text_output1.change(diff_texts,inputs=[text_output1,Grammar_text_output1],outputs=Diff_text_output1) | |
| Grammar_text_output2.change(diff_texts,inputs=[text_output2,Grammar_text_output2],outputs=Diff_text_output2) | |
| Grammar_text_output3.change(diff_texts,inputs=[text_link_output,Grammar_text_output3],outputs=Diff_text_output3) | |
| demo.launch() |