import os os.system("pip install git+https://github.com/openai/whisper.git") import gradio as gr import whisper from difflib import SequenceMatcher import re model = whisper.load_model("medium.en") def transcribe(file): options = dict(task="transcribe", best_of=5) text = model.transcribe(file, **options)["text"] return text.strip() with gr.Blocks() as demo: audio = gr.Audio( show_label=False, source="microphone", type="filepath" ) with gr.Row(): transcribe_button = gr.Button("Transcribe") sim_button = gr.Button("Similarity") textbox1 = gr.Textbox(show_label=False) transcribe_button.click(transcribe, inputs=[audio], outputs=[textbox1]) textbox2 = gr.Textbox(label="Enter the text to compare") label = gr.Label() def text_sim(par1, par2): sim = SequenceMatcher(None, par1, par2).ratio() * 100 return sim sim_button.click(text_sim, inputs=[textbox1, textbox2], outputs=label) demo.launch() #Nicy is awesome