deanna-emery commited on
Commit
b907f86
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1 Parent(s): 6a3746d
Files changed (1) hide show
  1. app.py +3 -3
app.py CHANGED
@@ -77,8 +77,8 @@ def translate(video_file, true_caption=None):
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  title = "American Sign Language Translation: An Approach Combining MoViNets and T5"
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  description = """
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- This application surfaces a model for translation of American Sign Language (ASL),
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- which comprises of a fine-tuned MoViNets CNN model and a T5 encoder-decoder model
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  to generate translations from the video embeddings. This model architecture achieves a BLEU score of 1.98
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  and an average cosine similarity score of 0.21 when trained and evaluated on the YouTube-ASL dataset.
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  More information about the model training and instructions to download the models can be found in our GitHub repository <a href=https://github.com/deanna-emery/ASL-Translator>here</a>.
@@ -108,7 +108,7 @@ article = """The captions for the example videos are as follows in order: \n
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  # Gradio App interface
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  gr.Interface(fn=translate,
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  inputs=[gr.Video(label='Video', show_label=True, max_length=10, sources='upload'),
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- gr.Textbox(label='Caption (optional)', show_label=True, interactive=False, visible=False)],
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  outputs="text",
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  allow_flagging="never",
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  title=title,
 
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  title = "American Sign Language Translation: An Approach Combining MoViNets and T5"
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  description = """
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+ This application surfaces a model for translation of American Sign Language (ASL).
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+ The model comprises of a fine-tuned MoViNet CNN model to generate video embeddings and a T5 encoder-decoder model
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  to generate translations from the video embeddings. This model architecture achieves a BLEU score of 1.98
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  and an average cosine similarity score of 0.21 when trained and evaluated on the YouTube-ASL dataset.
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  More information about the model training and instructions to download the models can be found in our GitHub repository <a href=https://github.com/deanna-emery/ASL-Translator>here</a>.
 
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  # Gradio App interface
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  gr.Interface(fn=translate,
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  inputs=[gr.Video(label='Video', show_label=True, max_length=10, sources='upload'),
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+ gr.Textbox(label='Caption', show_label=True, interactive=False, visible=False)],
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  outputs="text",
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  allow_flagging="never",
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  title=title,