app.py

import whisper

import gradio as gr 
import time


# You can choose your model from - see it on readme file and update the modelname
modelname = "large-v2"
model = whisper.load_model(modelname)

def SpeechToText(audio):
    if audio == None : return "" 
    time.sleep(1)

    audio = whisper.load_audio(audio)
    audio = whisper.pad_or_trim(audio)

    #  Decode audio to Text
    # options = whisper.DecodingOptions(fp16 = False)
    result = model.transcribe(audio, language="hy")
    return result["text"]


gr.Interface(
    title = 'OpenAI Whisper implementation on Gradio Web UI', 
    fn=SpeechToText, 
    
    inputs=[
        gr.Audio(source="microphone", type="filepath")
    ],
    outputs=[
        "textbox",
    ],
    live=True
).launch(
    debug=False,
    share=True
)