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English_To_Hindi_Audio_Translator

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Chandranshu Jain

Update app.py

f6c5e0e verified 3 months ago

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1.82 kB

	from transformers import pipeline
	import os
	import gradio as gr
	import torch
	from IPython.display import Audio as IPythonAudio
	from gtts import gTTS
	import IPython.display as ipd

	#Audio to text
	asr = pipeline(task="automatic-speech-recognition",
	model="distil-whisper/distil-small.en")
	#Text to text
	translator = pipeline(task="translation",
	model="facebook/nllb-200-distilled-600M",
	torch_dtype=torch.bfloat16)
	#Text to audio
	pipe = pipeline("text-to-speech", model="suno/bark-small",
	torch_dtype=torch.bfloat16)


	demo = gr.Blocks()
	def transcribe_speech(filepath):
	if filepath is None:
	gr.Warning("No audio found, please retry.")
	return ""
	output = translator(asr(filepath)["text"],
	src_lang="eng_Latn",
	tgt_lang="hin_Deva")
	narrated_text=pipe(output[0]['translation_text'])
	#tts = gTTS(text=narrated_text, lang='hi', slow=False)
	#tts.save("translated_audio.mp3")

	#return ipd.Audio("translated_audio.mp3", autoplay=True)
	return narrated_text

	mic_transcribe = gr.Interface(
	fn=transcribe_speech,
	inputs=gr.Audio(sources="microphone",
	type="filepath"),
	outputs="audio",
	#outputs=gr.Audio(label="Translated Message"),
	allow_flagging="never")

	file_transcribe = gr.Interface(
	fn=transcribe_speech,
	inputs=gr.Audio(sources="upload",
	type="filepath"),
	outputs="audio",
	#outputs=gr.Audio(label="Translated Message"),
	allow_flagging="never"
	)
	with demo:
	gr.TabbedInterface(
	[mic_transcribe,
	file_transcribe],
	["Transcribe Microphone",
	"Transcribe Audio File"],
	)

	demo.launch(share=True)
	demo.close()