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Jinjing Yi, Zach Hafen-Saavedra, William Craig, Tantrik Mukerji, Brady Ali Medina


Cat vocalizations (“meows”) are typically directed at humans, rather than other cats. Cat meows therefore present an opportunity for computational audio analysis to improve relationships between cats and their owners. In our analysis we developed an interface for users to upload audio recordings and have them interpreted as “comfortable”, “uncomfortable”, or “hungry”. Our classification leverages machine learning models trained on preprocessed and augmented data from the CatMeows dataset.

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