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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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## 💻 Usage
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First, install the repository from `github`.
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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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Check out the demo [here](https://huggingface.co/spaces/bpiyush/SoundOfWater). You can upload a video of pouring and the model estimates pitch and physical properties.
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## 💻 Usage
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First, install the repository from `github`.
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