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@@ -24,6 +24,7 @@ In this folder, we provide the following trained model checkpoints:
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  **TL;DR**: We present a method to infer physical properties of liquids from *just* the sound of pouring. We show in theory how *pitch* can be used to derive various physical properties such as container height, flow rate, etc. Then, we train a pitch detection network (`wav2vec2`) using simulated and real data. The resulting model can predict the physical properties of pouring liquids with high accuracy. The latent representations learned also encode information about liquid mass and container shape.
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  ## Demo
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  **TL;DR**: We present a method to infer physical properties of liquids from *just* the sound of pouring. We show in theory how *pitch* can be used to derive various physical properties such as container height, flow rate, etc. Then, we train a pitch detection network (`wav2vec2`) using simulated and real data. The resulting model can predict the physical properties of pouring liquids with high accuracy. The latent representations learned also encode information about liquid mass and container shape.
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+ Arxiv link: https://arxiv.org/abs/2411.11222
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  ## Demo
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