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from transformers import pipeline
import gradio as gr
from transformers import Wav2Vec2CTCTokenizer
preTrainedTokenizer = Wav2Vec2CTCTokenizer.from_pretrained("sukantan/wav2vec2-large-xls-r-300m-or-colab", unk_token="[UNK]", pad_token="[PAD]", word_delimiter_token="|", task="transcribe")
pipe = pipeline(model="sukantan/wav2vec2-large-xls-r-300m-or-colab", tokenizer=preTrainedTokenizer) # change to "your-username/the-name-you-picked"
def transcribe(audio):
text = pipe(audio)["text"]
text = text.replace("<s>", "")
return text
iface = gr.Interface(
fn=transcribe,
inputs=gr.Audio(source="microphone", type="filepath"),
outputs="text",
title="Wav2Vec2 Odia",
description="Realtime demo for Odia speech recognition using a fine-tuned wav2vec2-large-xls-r-300m model.",
)
iface.launch()
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