• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

灰海豹(Halichoerus grypus)能对叫声类别进行泛化吗?

Can a gray seal (Halichoerus grypus) generalize call classes?

作者信息

Stansbury Amanda L, de Freitas Mafalda, Wu Gi-Mick, Janik Vincent M

机构信息

Sea Mammal Research Unit, School of Biology, University of St. Andrews.

出版信息

J Comp Psychol. 2015 Nov;129(4):412-20. doi: 10.1037/a0039756. Epub 2015 Oct 12.

DOI:10.1037/a0039756
PMID:26460856
Abstract

Past researchers have found that gray seals (Halichoerus grypus) are capable of classifying vocal signals by call type using a trained set, but were unable to generalize to novel exemplars (Shapiro, Slater, & Janik, 2004). Given the importance of auditory categorization in communication, it would be surprising if the animals were unable to generalize acoustically similar calls into classes. Here, we trained a juvenile gray seal to discriminate novel calls into 2 classes, "growls" and "moans," by vocally matching call types (i.e., the seal moaned when played a moan and growled when played a growl). Our method differed from the previous study as we trained the animal using a comparatively large set of exemplars with standardized durations, consisting of both the seal's own calls and those of 2 other seals. The seal successfully discriminated growls and moans for both her own (94% correct choices) and the other seals' (87% correct choices) calls. We used a generalized linear model (GLM) and found that the seal's performance significantly improved across test sessions, and that accuracy was higher during the first presentation of a sound from her own repertoire but decreased after multiple exposures. This pattern was not found for calls from unknown seals. Factor analysis for mixed data (FAMD) identified acoustic parameters that could be used to discriminate between call types and individuals. Growls and moans differed in noise, duration and frequency parameters, whereas individuals differed only in frequency. These data suggest that the seal could have gained information about both call type and caller identity using frequency cues.

摘要

过去的研究人员发现,灰海豹(Halichoerus grypus)能够使用一组经过训练的信号,根据叫声类型对声音信号进行分类,但无法将其推广到新的样本中(夏皮罗、斯莱特和亚尼克,2004年)。鉴于听觉分类在交流中的重要性,如果动物无法将声学上相似的叫声归为一类,那将令人惊讶。在这里,我们训练了一只幼年灰海豹,通过声音匹配叫声类型,将新的叫声分为“咆哮”和“呻吟”两类(即播放呻吟声时海豹发出呻吟,播放咆哮声时海豹发出咆哮)。我们的方法与之前的研究不同,因为我们使用了一组相对较大的、具有标准化时长的样本对动物进行训练,这些样本包括海豹自己的叫声以及另外两只海豹的叫声。这只海豹成功地区分了自己的叫声(正确选择率为94%)和其他海豹的叫声(正确选择率为87%)中的咆哮声和呻吟声。我们使用了广义线性模型(GLM),发现这只海豹在测试过程中的表现显著提高,并且在首次播放其自身全部叫声中的声音时准确率更高,但在多次接触后准确率下降。对于来自未知海豹的叫声,没有发现这种模式。混合数据因子分析(FAMD)确定了可用于区分叫声类型和个体的声学参数。咆哮声和呻吟声在噪声、时长和频率参数方面存在差异,而个体之间仅在频率方面存在差异。这些数据表明,这只海豹可能利用频率线索获得了关于叫声类型和叫声者身份的信息。

相似文献

1
Can a gray seal (Halichoerus grypus) generalize call classes?灰海豹(Halichoerus grypus)能对叫声类别进行泛化吗?
J Comp Psychol. 2015 Nov;129(4):412-20. doi: 10.1037/a0039756. Epub 2015 Oct 12.
2
Call usage learning in gray seals (Halichoerus grypus).
J Comp Psychol. 2004 Dec;118(4):447-54. doi: 10.1037/0735-7036.118.4.447.
3
A gray seal's (Halichoerus grypus) responses to experimenter-given pointing and directional cues.
J Comp Psychol. 2003 Dec;117(4):355-62. doi: 10.1037/0735-7036.117.4.355.
4
Source levels of the underwater calls of a male leopard seal.雄性豹海豹水下叫声的源级
J Acoust Soc Am. 2014 Oct;136(4):1495-8. doi: 10.1121/1.4895685.
5
The role of vocal learning in call acquisition of wild grey seal pups.在野生灰海豹幼崽叫声习得中的发声学习作用。
Philos Trans R Soc Lond B Biol Sci. 2021 Oct 25;376(1836):20200251. doi: 10.1098/rstb.2020.0251. Epub 2021 Sep 6.
6
Formant Modification through Vocal Production Learning in Gray Seals.通过灰海豹的发声学习来改变共振峰。
Curr Biol. 2019 Jul 8;29(13):2244-2249.e4. doi: 10.1016/j.cub.2019.05.071. Epub 2019 Jun 20.
7
Repetition patterns in Weddell seal (Leptonychotes weddellii) underwater multiple element calls.威德尔海豹(Leptonychotes weddellii)水下多元素叫声中的重复模式。
J Acoust Soc Am. 2004 Aug;116(2):1261-70. doi: 10.1121/1.1763956.
8
Antimasking aspects of harp seal (Pagophilus groenlandicus) underwater vocalizations.竖琴海豹(Pagophilus groenlandicus)水下发声的抗掩蔽特性。
J Acoust Soc Am. 2002 Dec;112(6):3083-90. doi: 10.1121/1.1518987.
9
Acoustic analysis of crabeater seal (Lobodon carcinophaga) vocalizations in the Southern Kerguelen Plateau region of East Antarctica.东南极南设得兰群岛地区食蟹海豹(Lobodon carcinophaga)叫声的声学分析。
J Acoust Soc Am. 2021 Nov;150(5):3353. doi: 10.1121/10.0006789.
10
Vocal usage learning and vocal comprehension learning in harbor seals.海豹的发声使用学习和发声理解学习。
BMC Neurosci. 2024 Oct 4;25(1):48. doi: 10.1186/s12868-024-00899-4.

引用本文的文献

1
Vocal usage learning and vocal comprehension learning in harbor seals.海豹的发声使用学习和发声理解学习。
BMC Neurosci. 2024 Oct 4;25(1):48. doi: 10.1186/s12868-024-00899-4.
2
PyGellermann: a Python tool to generate pseudorandom series for human and non-human animal behavioural experiments.PyGellermann:一个用于生成人类和非人类动物行为实验伪随机序列的 Python 工具。
BMC Res Notes. 2023 Jul 5;16(1):135. doi: 10.1186/s13104-023-06396-x.
3
Vocal production learning in mammals revisited.哺乳动物发声学习的再思考。
Philos Trans R Soc Lond B Biol Sci. 2021 Oct 25;376(1836):20200244. doi: 10.1098/rstb.2020.0244. Epub 2021 Sep 6.
4
The multi-dimensional nature of vocal learning.发声学习的多维性。
Philos Trans R Soc Lond B Biol Sci. 2021 Oct 25;376(1836):20200236. doi: 10.1098/rstb.2020.0236. Epub 2021 Sep 6.
5
What Pinnipeds Have to Say about Human Speech, Music, and the Evolution of Rhythm.鳍足类动物对人类语言、音乐及节奏进化的见解
Front Neurosci. 2016 Jun 20;10:274. doi: 10.3389/fnins.2016.00274. eCollection 2016.