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import logging
import warnings
import gradio as gr
from transformers import pipeline
from transformers.utils.logging import disable_progress_bar
warnings.filterwarnings("ignore")
disable_progress_bar()
logging.basicConfig(
format="%(asctime)s [%(levelname)s] [%(name)s] %(message)s",
datefmt="%Y-%m-%dT%H:%M:%SZ",
)
logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)
pipe = pipeline(model="bofenghuang/asr-wav2vec2-ctc-french")
logger.info("ASR pipeline has been initialized")
def transcribe(audio):
# text = pipe(audio, chunk_length_s=30, stride_length_s=5)["text"]
text = pipe(audio)["text"]
logger.info(f"Transcription for {audio}: {text}")
return text
iface = gr.Interface(
fn=transcribe,
inputs=gr.Audio(source="upload", type="filepath", label="Upload some audio file..."),
outputs="text",
title="Speech-to-Text in French",
description="Realtime demo for French automatic speech recognition.",
allow_flagging="never",
)
# iface.launch(server_name="0.0.0.0", debug=True, share=True)
iface.launch()
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