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<p>Accurate age estimation is essential for advancing interspecies communication but remains a challenge across non-human species. This study presents the first dataset of domestic feline vocalisations specifically designed for age prediction and introduces a novel deep learning pipeline for this purpose. By applying transfer learning with models like VGGish, YAMNet, and Perch, we demonstrate the potential for automated age classification, with VGGish achieving the best results. Our findings hold significant potential for applications in veterinary care and wildlife conservation, building on existing research and pushing forward the boundaries of automated age classification within digital bioacoustics. Future work could explore improving model generalisability and robustness, potentially expanding its application across species.</p>

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A deep learning pipeline for age prediction from vocalisations of the domestic feline

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月3日

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  • Astrid van Toor,
  • Nadeem Qazi,
  • Stefania Paladini

摘要

Accurate age estimation is essential for advancing interspecies communication but remains a challenge across non-human species. This study presents the first dataset of domestic feline vocalisations specifically designed for age prediction and introduces a novel deep learning pipeline for this purpose. By applying transfer learning with models like VGGish, YAMNet, and Perch, we demonstrate the potential for automated age classification, with VGGish achieving the best results. Our findings hold significant potential for applications in veterinary care and wildlife conservation, building on existing research and pushing forward the boundaries of automated age classification within digital bioacoustics. Future work could explore improving model generalisability and robustness, potentially expanding its application across species.