The potential for acoustic individual identification in mammals

Pavel Linhart, Mathieu Mahamoud-Issa, Dan Stowell, Daniel T. Blumstein

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)


Many studies have revealed that animal vocalizations, including those from mammals, are individually distinctive. Therefore, acoustic identification of individuals (AIID) has been repeatedly suggested as a non-invasive and labor efficient alternative to mark-recapture identification methods. We present a pipeline of steps for successful AIID in a given species. By conducting such work, we will also improve our understanding of identity signals in general. Strong and stable acoustic signatures are necessary for successful AIID. We reviewed studies of individual variation in mammalian vocalizations as well as pilot studies using acoustic identification to census mammals and birds. We found the greatest potential for AIID (characterized by strong and stable acoustic signatures) was in Cetacea and Primates (including humans). In species with weaker acoustic signatures, AIID could still be a valuable tool once its limitations are fully acknowledged. A major obstacle for widespread utilization of AIID is the absence of tools integrating all AIID subtasks within a single package. Automation of AIID could be achieved with the use of advanced machine learning techniques inspired by those used in human speaker recognition or tailored to specific challenges of animal AIID. Unfortunately, further progress in this area is currently hindered by the lack of appropriate publicly available datasets. However, we believe that after overcoming the issues outlined above, AIID can quickly become a widespread and valuable tool in field research and conservation of mammals and other animals.
Original languageEnglish
Pages (from-to)667–683
Number of pages17
JournalMammalian Biology
Early online date31 Mar 2022
Publication statusPublished - 31 Mar 2022


  • Acoustic communication
  • Acoustic individual identification (AIID)
  • Acoustic signature
  • Individual identity
  • Individual variation
  • Machine learning
  • Mammal
  • Vocalizations


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