app.py

import gradio as gr

import nemo.collections.asr as nemo_asr


asr_model = nemo_asr.models.EncDecCTCModelBPE. \
                    from_pretrained("theodotus/stt_uk_squeezeformer_ctc_xs",map_location="cpu")



def transcribe(audio):
    text = asr_model.transcribe([audio], batch_size=1)[0]
    return text


gr.Interface(
    fn=transcribe, 
    inputs=gr.Audio(source="microphone", type="filepath"), 
    outputs="text").launch()