A Whisker of Truth: A Multimodal Interdisciplinary Machine Learning Approach to Vocal, Visual, and Tactile Signals in the Domestic Cat

We propose a multimodal deep learning framework for automated analysis of cat–human communication, integrating acoustic, visual, and tactile signals through transformer-based fusion. Using the largest expert-annotated dataset of its kind and interdisciplinary collaboration, we combine semi-supervised learning with ethological and phonetic expertise to detect subtle behavioural and phonetic cues, enable early welfare assessment, and establish species-generalisable methods.