Individual identification in acoustic recordings

Individual acoustic signatures, if present within animal species, can provide insights into evolution and behavior, and have great potential for differentiating individuals during monitoring and research. Recent advances in bioacoustic technology combined with acoustic individual identification (AIID) have the potential to revolutionize the study of sound-producing animals; however, methods and application of AIID remain in their infancy. Evidence of individual acoustic signatures across taxa and successes in adjacent acoustic disciplines suggest that opportunities exist for developing AIID. Research and development into AIID should combine deep learning methods with the construction and sharing of labeled training datasets, and should focus on recording and classification methods that maximize the potential applications of AIID. Broadscale implementation of AIID should be achievable in the near future and will allow biologists to answer important ecological and evolutionary questions with less bias and fewer negative population effects and resources than the current approaches.