PhysHunter commited on
Commit
748ad62
·
1 Parent(s): ee3d3d0

Update app.py

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Files changed (1) hide show
  1. app.py +3 -4
app.py CHANGED
@@ -1,7 +1,6 @@
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  import gradio as gr
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  import numpy as np
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  import torch
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- from datasets import load_dataset
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  from transformers import VitsModel, VitsTokenizer, pipeline
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  device = "cuda:0" if torch.cuda.is_available() else "cpu"
@@ -33,7 +32,7 @@ def speech_to_speech_translation(audio):
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  return 16000, synthesised_speech
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- # title = "Cascaded STST"
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  # description = """
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  # Demo for cascaded speech-to-speech translation (STST), mapping from source speech in any language to target speech in French. Demo uses OpenAI's [Whisper Base](https://huggingface.co/openai/whisper-base) model for speech translation, and Facebook's
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  # [MMS TTS](https://huggingface.co/facebook/mms-tts) model for text-to-speech:
@@ -47,7 +46,7 @@ mic_translate = gr.Interface(
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  inputs=gr.Audio(source="microphone", type="filepath"),
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  outputs=gr.Audio(label="Generated Speech", type="numpy"),
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  title=title,
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- description=description,
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  )
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  file_translate = gr.Interface(
@@ -56,7 +55,7 @@ file_translate = gr.Interface(
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  outputs=gr.Audio(label="Generated Speech", type="numpy"),
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  examples=[["./example.wav"]],
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  title=title,
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- description=description,
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  )
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  with demo:
 
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  import gradio as gr
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  import numpy as np
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  import torch
 
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  from transformers import VitsModel, VitsTokenizer, pipeline
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  device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
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  return 16000, synthesised_speech
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+ title = "Cascaded STST"
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  # description = """
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  # Demo for cascaded speech-to-speech translation (STST), mapping from source speech in any language to target speech in French. Demo uses OpenAI's [Whisper Base](https://huggingface.co/openai/whisper-base) model for speech translation, and Facebook's
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  # [MMS TTS](https://huggingface.co/facebook/mms-tts) model for text-to-speech:
 
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  inputs=gr.Audio(source="microphone", type="filepath"),
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  outputs=gr.Audio(label="Generated Speech", type="numpy"),
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  title=title,
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+ #description=description,
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  )
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  file_translate = gr.Interface(
 
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  outputs=gr.Audio(label="Generated Speech", type="numpy"),
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  examples=[["./example.wav"]],
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  title=title,
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+ #description=description,
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  )
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  with demo: