app.py

from transformers import pipeline
import gradio as gr

transcribe = pipeline(
    task="automatic-speech-recognition",
    model="ckpt_large_v2/checkpoint-1740",
    tokenizer="ckpt_large_v2",
    chunk_length_s=30,
    device=-1,
)

transcribe.model.config.forced_decoder_ids = transcribe.tokenizer.get_decoder_prompt_ids(language="ja", task="transcribe")
def main(audio_path):
    return transcribe(audio_path)["text"]


with open('./README.md') as f:
    md = f.readlines()
    md = md[11:]
    md = "\n".join(md)

iface = gr.Interface(
  fn=main,
  inputs=[gr.Audio(type='filepath',sources=['microphone','upload'])],
  description=md,
  outputs="text",
  title="CoCoCap-beta 日本語声質キャプショニンング with CocoNut Corpus",
).launch(share=True)