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import gradio as gr
import whisper
from langcodes import *
def speech_to_text(tmp_filename, uploaded, model_size):
model = whisper.load_model(model_size)
source = uploaded if uploaded is not None else tmp_filename
result = model.transcribe(source)
return f'Detected language: {Language.make(language=result["language"]).display_name()}\n\n You said: {result["text"]}'
gr.Interface(
title="",
thumbnail="",
css="""
footer {visibility: hidden}
.gr-prose p{text-align: center;}
.gr-button {background: black;color: white}
""",
description="",
fn=speech_to_text,
inputs=[
gr.Audio(source="upload", type="filepath", label="Upload Audio"),
gr.Dropdown(label="Select model size",value="base",choices=["tiny", "base", "small", "medium", "large"])],
outputs="text").launch() |