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import gradio as gr |
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from asr import transcribe, ASR_EXAMPLES, ASR_LANGUAGES, ASR_NOTE |
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mms_transcribe = gr.Interface( |
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fn=transcribe, |
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inputs=[ |
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gr.Audio(), |
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gr.Dropdown( |
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[f"{k} ({v})" for k, v in ASR_LANGUAGES.items()], |
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label="Language", |
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value="eng English", |
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), |
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], |
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outputs="text", |
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examples=ASR_EXAMPLES, |
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title="Speech-to-text", |
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description=( |
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"Transcribe audio from a microphone or input file in your desired language." |
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), |
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article=ASR_NOTE, |
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allow_flagging="never", |
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) |
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with gr.Blocks() as demo: |
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gr.HTML( |
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""" |
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<div style="text-align: center;"> |
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<img src="https://huggingface.co/spaces/facebook/MMS/resolve/main/BANNER.png" alt="UNESCO Meta Hugging Face Banner" style="max-width: 800px; width: 100%; margin: 0 auto;"> |
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<h1 style="color: #0077be;">Language Transcriber powered by UNESCO, Meta and Hugging Face</h1> |
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</div> |
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""" |
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) |
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gr.Markdown( |
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"<p align='center' style='font-size: 20px;'>MMS: Scaling Speech Technology to 1000+ languages demo. See our <a href='https://ai.facebook.com/blog/multilingual-model-speech-recognition/'>blog post</a> and <a href='https://arxiv.org/abs/2305.13516'>paper</a>.</p>" |
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) |
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gr.HTML( |
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"""<center>You can also finetune MMS models on your data using the recipes provides <a href='https://huggingface.co/blog/mms_adapters'>here</a>.</center>""" |
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) |
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gr.HTML( |
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"""<center><a href="https://huggingface.co/spaces/facebook/MMS?duplicate=true" style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank"><img style="margin-bottom: 0em;display: inline;margin-top: -.25em;" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> for more control and no queue.</center>""" |
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) |
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mms_transcribe.render() |
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gr.HTML( |
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""" |
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<div class="footer" style="text-align:center"> |
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<p> |
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Model by <a href="https://ai.facebook.com" style="text-decoration: underline;" target="_blank">Meta AI</a> - Gradio Demo by 🤗 Hugging Face |
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</p> |
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</div> |
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""" |
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) |
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if __name__ == "__main__": |
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demo.queue() |
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demo.launch() |
