Tonic commited on
Commit
989551b
1 Parent(s): b9db94a

Update app.py

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Files changed (1) hide show
  1. app.py +30 -2
app.py CHANGED
@@ -5,6 +5,15 @@ import os
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  import time
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  import soundfile as sf
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  # Define the list of target languages
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  languages = {
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  "English": "eng",
@@ -14,15 +23,33 @@ languages = {
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  "Spanish": "spa"
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  }
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  def speech_to_text(audio_data, tgt_lang):
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- audio_input, _ = torchaudio.load(audio_data)
 
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  s2t_model = torch.jit.load("unity_on_device_s2t.ptl")
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  with torch.no_grad():
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  text = s2t_model(audio_input, tgt_lang=languages[tgt_lang])
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  return text
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  def speech_to_speech_translation(audio_data, tgt_lang):
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- audio_input, _ = torchaudio.load(audio_data)
 
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  s2st_model = torch.jit.load("unity_on_device.ptl")
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  with torch.no_grad():
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  text, units, waveform = s2st_model(audio_input, tgt_lang=languages[tgt_lang])
@@ -31,6 +58,7 @@ def speech_to_speech_translation(audio_data, tgt_lang):
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  return text, output_file
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  def create_interface():
 
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  with gr.Blocks(theme='ParityError/Anime') as interface:
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  # Dropdown for language selection
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  input_language = gr.Dropdown(list(languages.keys()), label="Select Target Language", value="English")
 
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  import time
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  import soundfile as sf
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+ welcome_message = """
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+ # 👋🏻Welcome to 🔥Tonic's🗣️Unity On Device!🚀
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+
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+ 🔥Tonic's🗣️Unity On Device!🚀 uses [facebook/seamless-m4t-unity-small](https://huggingface.co/facebook/seamless-m4t-unity-small) for audio translation & accessibility.
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+ 🔥Tonic's🗣️Unity On Device!🚀 on your own data & in your own way by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/TeamTonic/SeamlessOnDevice?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3>
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+ ### Join us :
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+ 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community on 👻Discord: [Discord](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [PolyGPT](https://github.com/tonic-ai/polygpt-alpha)"
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+ """
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+
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  # Define the list of target languages
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  languages = {
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  "English": "eng",
 
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  "Spanish": "spa"
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  }
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+ def save_audio(audio_input, output_dir="saved_audio"):
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+ if not os.path.exists(output_dir):
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+ os.makedirs(output_dir)
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+
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+ # Extract sample rate and audio data
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+ sample_rate, audio_data = audio_input
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+
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+ # Generate a unique file name
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+ file_name = f"audio_{int(time.time())}.wav"
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+ file_path = os.path.join(output_dir, file_name)
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+
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+ # Save the audio file
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+ sf.write(file_path, audio_data, sample_rate)
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+
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+ return file_path
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+
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  def speech_to_text(audio_data, tgt_lang):
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+ file_path = save_audio(audio_data)
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+ audio_input, _ = torchaudio.load(file_path)
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  s2t_model = torch.jit.load("unity_on_device_s2t.ptl")
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  with torch.no_grad():
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  text = s2t_model(audio_input, tgt_lang=languages[tgt_lang])
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  return text
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  def speech_to_speech_translation(audio_data, tgt_lang):
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+ file_path = save_audio(audio_data)
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+ audio_input, _ = torchaudio.load(file_path)
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  s2st_model = torch.jit.load("unity_on_device.ptl")
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  with torch.no_grad():
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  text, units, waveform = s2st_model(audio_input, tgt_lang=languages[tgt_lang])
 
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  return text, output_file
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  def create_interface():
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+ with gr.Markdown(welcome_message)
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  with gr.Blocks(theme='ParityError/Anime') as interface:
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  # Dropdown for language selection
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  input_language = gr.Dropdown(list(languages.keys()), label="Select Target Language", value="English")