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| # Module Imports | |
| from pytube import YouTube | |
| import whisper | |
| import gradio as gr | |
| model = whisper.load_model("base.en") | |
| # Functions | |
| def transcribe(file): | |
| options = dict(task="transcribe", best_of=5) | |
| text = model.transcribe(file, **options)["text"] | |
| return text.strip() | |
| def translate(file): | |
| options = dict(task="translate", best_of=5) | |
| text = model.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 = model.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 = model.transcribe(file, **options)["text"] | |
| return text.strip() | |
| # 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") | |
| transcribe_button1 = gr.Button("Transcribe") | |
| CG_button1 = gr.Button("Check Grammar (Work In Progress)") | |
| with gr.TabItem("Upload File"): | |
| with gr.Row(): | |
| file_upload = gr.File() | |
| text_output2 = gr.Textbox(label="Transcription", placeholder="Text Output") | |
| transcribe_button2 = gr.Button("Transcribe") | |
| CG_button3 = gr.Button("Check Grammar (Work In Progress)") | |
| 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") | |
| CG_button3 = gr.Button("Check Grammar (Work In Progress)") | |
| with gr.TabItem("About"): | |
| with gr.Row(): | |
| gr.Markdown(""" | |
| <p style="text-align: center;"> Thesis System presented by <br/> <br/> | |
| • <b>Jomari A. Buenaobra</b> <br/> | |
| • <b>Christian G. Eslit</b> <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>Jonardo R. Asor</b> - Subject Specialist <br/> | |
| </p> | |
| """) | |
| link.change(populate_metadata, inputs=[link], outputs=[img, title]) | |
| 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) | |
| demo.launch() |