app.py

from transformers import pipeline, AutoFeatureExtractor, AutoTokenizer, Wav2Vec2ForCTC
import gradio as gr
import time

model_id = 'comodoro/wav2vec2-xls-r-300m-cs-250'
feature_extractor = AutoFeatureExtractor.from_pretrained(model_id)
model = Wav2Vec2ForCTC.from_pretrained(model_id)
tokenizer = AutoTokenizer.from_pretrained(model_id)

p = pipeline("automatic-speech-recognition", chunk_length_s=5, model=model, 
    tokenizer=tokenizer, feature_extractor=feature_extractor)

def transcribe(audio, state=""):
    time.sleep(2)
    text = p(audio)["text"]
    state += text + " "
    return state, state

gr.Interface(
    fn=transcribe, 
    inputs=[
        gr.inputs.Audio(source="microphone", type="filepath"), 
        "state"
    ],
    outputs=[
        "textbox",
        "state"
    ],
    live=True).launch(debug=True)