Chandranshu Jain
commited on
Commit
•
3603b99
1
Parent(s):
6ac32df
Create app.py
Browse files
app.py
ADDED
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from transformers import pipeline
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import os
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import gradio as gr
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import torch
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from IPython.display import Audio as IPythonAudio
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#Audio to text
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asr = pipeline(task="automatic-speech-recognition",
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model="distil-whisper/distil-small.en")
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#Text to text
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translator = pipeline(task="translation",
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model="facebook/nllb-200-distilled-600M",
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torch_dtype=torch.bfloat16)
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#Text to audio
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pipe = pipeline("text-to-speech", model="suno/bark-small")
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demo = gr.Blocks()
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def transcribe_speech(filepath):
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if filepath is None:
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gr.Warning("No audio found, please retry.")
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return ""
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output = translator(asr(filepath)["text"],
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src_lang="eng_Latn",
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tgt_lang="hin_Deva")
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narrated_text=pipe(output[0]['translation_text'])
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output=IPythonAudio(narrated_text["audio"][0],
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rate=narrated_text["sampling_rate"])
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return output
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mic_transcribe = gr.Interface(
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fn=transcribe_speech,
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inputs=gr.Audio(sources="microphone",
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type="filepath"),
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outputs=gr.Audio(label="Translated Message"),
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allow_flagging="never")
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file_transcribe = gr.Interface(
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fn=transcribe_speech,
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inputs=gr.Audio(sources="upload",
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type="filepath"),
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outputs=gr.Audio(label="Translated Message"),
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allow_flagging="never",
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)
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with demo:
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gr.TabbedInterface(
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[mic_transcribe,
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file_transcribe],
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["Transcribe Microphone",
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"Transcribe Audio File"],
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)
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demo.launch(share=True)
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demo.close()
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