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

van Toor, Astrid ; Schötz, Susanne LU orcid and Hirsch, Elin LU (2025) p.1-8
Abstract
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.
Abstract (Swedish)
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.
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Contribution to conference
publication status
published
subject
pages
1 - 8
project
Melody in human–cat communication
Interspecific Communication ASG, Pufendorf IAS
Cat-human communication: vocal, visual and tactile signals
language
English
LU publication?
yes
id
18106a7a-f7a0-4be1-ad8d-fa3bbaca225d
alternative location
https://openreview.net/attachment?id=HIkzPhD0Zo&name=pdf
date added to LUP
2026-01-13 10:14:46
date last changed
2026-01-14 07:36:53
@misc{18106a7a-f7a0-4be1-ad8d-fa3bbaca225d,
  abstract     = {{We propose a multimodal deep learning framework for automated analysis of<br/>cat–human communication, integrating acoustic, visual, and tactile signals through<br/>transformer-based fusion. Using the largest expert-annotated dataset of its kind<br/>and interdisciplinary collaboration, we combine semi-supervised learning with<br/>ethological and phonetic expertise to detect subtle behavioural and phonetic cues,<br/>enable early welfare assessment, and establish species-generalisable methods.}},
  author       = {{van Toor, Astrid and Schötz, Susanne and Hirsch, Elin}},
  language     = {{eng}},
  pages        = {{1--8}},
  title        = {{A Whisker of Truth: A Multimodal Interdisciplinary Machine Learning Approach to Vocal, Visual, and Tactile Signals in the Domestic Cat}},
  url          = {{https://lup.lub.lu.se/search/files/239402649/6_A_Whisker_of_Truth_A_Multimo.pdf}},
  year         = {{2025}},
}