Tchernichovski O, Lints T J, Deregnaucourt S, Cimenser A, Mitra P P
Department of Biology, City College of the City University of New York, NY 10031, USA.
Ann N Y Acad Sci. 2004 Jun;1016:348-63. doi: 10.1196/annals.1298.031.
Current technology makes it possible to measure song development continuously throughout a vocal ontogeny. Here we briefly review some of the problems involved and describe experimental and analytic methods for automatic tracing of vocal changes. These techniques make it possible to characterize the specific methods the bird uses to imitate sounds: an automated song recognition procedure allows continuous song recording, followed by automated sound analysis that partition the song to syllables, extract acoustic features of each syllable, and summarize the entire song development process over time into a single database. The entire song development is then presentable in the form of images or movie clips. These Dynamic Vocal Development (DVD) maps show how each syllable type emerges, and how the bird manipulates syllable features to eventually approximate the model song. Most of the experimental and analytic methods described here have been organized into a software package, which also allows combined neural and sound recording to monitor changes in brain activity as vocal learning occurs. The software is available at http://ofer.sci.ccny.cuny.edu.
当前技术使得在整个发声个体发育过程中持续测量鸣叫发展成为可能。在此,我们简要回顾一些相关问题,并描述用于自动追踪发声变化的实验和分析方法。这些技术能够刻画鸟类模仿声音所使用的具体方法:一种自动鸣叫识别程序可进行连续的鸣叫记录,随后进行自动声音分析,将鸣叫分割为音节,提取每个音节的声学特征,并随时间将整个鸣叫发展过程汇总到一个单一数据库中。然后,整个鸣叫发展过程可以以图像或电影片段的形式呈现出来。这些动态发声发展(DVD)图谱展示了每种音节类型是如何出现的,以及鸟类如何操纵音节特征最终接近示范鸣叫。这里描述的大多数实验和分析方法已被整合到一个软件包中,该软件包还允许同时进行神经和声音记录,以监测发声学习过程中大脑活动的变化。该软件可在http://ofer.sci.ccny.cuny.edu获取。