Technological advances for getting insight into the learning capacities of birds in the vocal domain

IF 0.9 4区 心理学 Q3 COMMUNICATION Interaction Studies Pub Date : 2023-11-03 DOI:10.1075/is.22043.der
Sébastien Derégnaucourt, Alice Araguas, Bahia Guellaï
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Abstract

Abstract Birds produce different types of sounds in different contexts such as begging for food in youngsters, alerting to a danger, defending a territory or attracting a sexual partner. About half of the bird species are able to transform their vocalizations through imitation, improvisation or invention of sounds. Here we review the different experimental procedures that have been used to study the learning capacities of birds in the vocal domain and in the auditory domain, with a particular emphasis on recent technological developments. Nowadays, it is possible to record individual vocalizations of birds living in social groups or to record continuously the vocal ontogeny of birdsong. In conditioning experiments, new paradigms have successfully replaced food rewards with a socio-sexual reward. It is possible to engage in vocal interactions with a bird using dedicated computer systems. In both the laboratory and more recently in the field, different techniques have been used to train young oscine songbirds to learn from acoustic models. The use of virtual social environments and robots as social agents are also promising avenues. All together, these new techniques will permit researchers to explore more deeply the umwelt of bird species.
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深入了解鸟类在声音领域的学习能力的技术进步
鸟类在不同的环境中会发出不同类型的声音,比如幼鸟乞求食物、警告危险、保卫领地或吸引性伴侣。大约一半的鸟类能够通过模仿、即兴创作或发明声音来改变它们的发声方式。在这里,我们回顾了用于研究鸟类在声音领域和听觉领域学习能力的不同实验程序,特别强调了最近的技术发展。如今,可以记录群居鸟类的个体发声,也可以连续记录鸟类鸣叫的发声本体论。在条件反射实验中,新的范例已经成功地用社会性奖励取代了食物奖励。利用专用的计算机系统,与鸟类进行声音互动是可能的。在实验室和最近的实地研究中,不同的技术被用来训练年轻的鸣禽从声学模型中学习。使用虚拟社会环境和机器人作为社会代理也是很有前途的途径。总之,这些新技术将使研究人员能够更深入地探索鸟类的生存环境。
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来源期刊
CiteScore
3.30
自引率
6.70%
发文量
8
期刊介绍: This international peer-reviewed journal aims to advance knowledge in the growing and strongly interdisciplinary area of Interaction Studies in biological and artificial systems. Understanding social behaviour and communication in biological and artificial systems requires knowledge of evolutionary, developmental and neurobiological aspects of social behaviour and communication; the embodied nature of interactions; origins and characteristics of social and narrative intelligence; perception, action and communication in the context of dynamic and social environments; social learning.
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