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Update app.py

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  1. app.py +3 -3
app.py CHANGED
@@ -30,10 +30,10 @@ with gr.Blocks() as demo:
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  with gr.Column(scale=2):
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  gr.Markdown(
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  """
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- # WhiStress: Enriching Transcriptions with Sentence Stress Detection
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  The WhiStress model allows you to detect important words in your speech.
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- Check out our paper: πŸ“š [WhiStress](https://arxiv.org/),
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  ## Architecture
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  The model is built on [Whisper](https://arxiv.org/abs/2212.04356) model,
@@ -42,7 +42,7 @@ with gr.Blocks() as demo:
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  WhiStress includes an additional decoder based classifier that predicts the stress label of each transcription token.
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  ## Training Data
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- The model was trained using [TinyStress-15K](https://huggingface.co/datasets/loud-whisper-project/tinyStories-audio-emphasized),
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  that is derived from [tinyStories](https://huggingface.co/datasets/roneneldan/TinyStories) dataset.
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  ## Inference Demo
 
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  with gr.Column(scale=2):
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  gr.Markdown(
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  """
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+ # ***WhiStress***: Enriching Transcriptions with Sentence Stress Detection
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  The WhiStress model allows you to detect important words in your speech.
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+ Check out our paper: πŸ“š [***WhiStress***](https://arxiv.org/)
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  ## Architecture
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  The model is built on [Whisper](https://arxiv.org/abs/2212.04356) model,
 
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  WhiStress includes an additional decoder based classifier that predicts the stress label of each transcription token.
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  ## Training Data
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+ The model was trained using [***TinyStress-15K***](https://huggingface.co/datasets/slprl/TinyStress-15K),
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  that is derived from [tinyStories](https://huggingface.co/datasets/roneneldan/TinyStories) dataset.
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  ## Inference Demo