How learning affects vocalizations is a key question in the study of animal communication and human language. Parallel efforts in birds and humans have taught us much about how vocal learning works on a behavioural and neurobiological level. Subsequent efforts have revealed a variety of cases among mammals in which experience also has a major influence on vocal repertoires. Janik and Slater (Anim. Behav.60, 1–11. (doi:10.1006/anbe.2000.1410)) introduced the distinction between vocal usage and production learning, providing a general framework to categorize how different types of learning influence vocalizations. This idea was built on by Petkov and Jarvis (Front. Evol. Neurosci.4, 12. (doi:10.3389/fnevo.2012.00012)) to emphasize a more continuous distribution between limited and more complex vocal production learners. Yet, with more studies providing empirical data, the limits of the initial frameworks become apparent. We build on these frameworks to refine the categorization of vocal learning in light of advances made since their publication and widespread agreement that vocal learning is not a binary trait. We propose a novel classification system, based on the definitions by Janik and Slater, that deconstructs vocal learning into key dimensions to aid in understanding the mechanisms involved in this complex behaviour. We consider how vocalizations can change without learning, and a usage learning framework that considers context specificity and timing. We identify dimensions of vocal production learning, including the copying of auditory models (convergence/divergence on model sounds, accuracy of copying), the degree of change (type and breadth of learning) and timing (when learning takes place, the length of time it takes and how long it is retained). We consider grey areas of classification and current mechanistic understanding of these behaviours. Our framework identifies research needs and will help to inform neurobiological and evolutionary studies endeavouring to uncover the multi-dimensional nature of vocal learning.

This article is part of the theme issue ‘Vocal learning in animals and humans’.

学习如何影响发声是动物交流和人类语言研究中的一个关键问题。鸟类和人类的平行研究让我们了解了声音学习如何在行为和神经生物学水平上发挥作用。随后的努力揭示了哺乳动物中的各种案例，其中经验也对声乐曲目产生重大影响。Janik 和 Slater ( Anim. Behav. 60 , 1-11. (doi:10.1006/anbe.2000.1410)) 介绍了声乐使用和生产学习之间的区别，提供了一个通用框架来分类不同类型的学习如何影响发声。这个想法是由 Petkov 和 Jarvis ( Front. Evol. Neurosci. 4, 12. (doi:10.3389/fnevo.2012.00012)) 强调有限和更复杂的发声学习者之间的更连续分布。然而，随着更多研究提供经验数据，初始框架的局限性变得明显。我们在这些框架的基础上，根据自出版以来取得的进展以及声乐学习不是二元特征的广泛共识，完善声乐学习的分类。我们基于 Janik 和 Slater 的定义提出了一种新的分类系统，它将声音学习解构为关键维度，以帮助理解这种复杂行为所涉及的机制。我们考虑了发声如何在没有学习的情况下发生变化，以及一个考虑上下文特异性和时间的使用学习框架。我们确定了声乐制作学习的维度，包括听觉模型的复制（模型声音的收敛/发散、复制的准确性）、变化程度（学习的类型和广度）和时间（学习发生的时间、花费的时间长度以及保留多长时间） ）。我们考虑分类的灰色区域和当前对这些行为的机械理解。我们的框架确定了研究需求，并将有助于为神经生物学和进化研究提供信息，努力揭示声乐学习的多维性质。我们考虑分类的灰色区域和当前对这些行为的机械理解。我们的框架确定了研究需求，并将有助于为神经生物学和进化研究提供信息，努力揭示声乐学习的多维性质。我们考虑分类的灰色区域和当前对这些行为的机械理解。我们的框架确定了研究需求，并将有助于为神经生物学和进化研究提供信息，努力揭示声乐学习的多维性质。

这篇文章是主题问题“动物和人类的声乐学习”的一部分。