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