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首页> 外文期刊>Philosophical Transactions of the Royal Society of London, Series B. Biological Sciences >Splits or waves? flees or webs? How divergence measures and network analysis can unravel language histories
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Splits or waves? flees or webs? How divergence measures and network analysis can unravel language histories

机译:分裂还是波浪?逃跑或网?差异度量和网络分析如何揭示语言历史

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Linguists have traditionally represented patterns of divergence within a language family in terms of either a 'splits' model, corresponding to a branching family tree structure, or the wave model, resulting in a (dialect) continuum. Recent phylogenetic analyses, however, have tended to assume the former as a viable idealization also for the latter. But the contrast matters, for it typically reflects different processes in the real world: speaker populations either separated by migrations, or expanding over continuous territory. Since history often leaves a complex of both patterns within the same language family, ideally we need a single model to capture both, and tease apart the respective contributions of each. The 'network' type of phylogenetic method offers this, so we review recent applications to language data. Most have used lexical data, encoded as binary or multi-state characters. We look instead at continuous distance measures of divergence in phonetics. Our output networks combine branch- and continuum-like signals in ways that correspond well to known histories (illustrated for Germanic, and particularly English). We thus challenge the traditional insistence on shared innovations, setting out a new, principled explanation for why complex language histories can emerge correctly from distance measures, despite shared retentions and parallel innovations.
机译:语言学家传统上用“分裂”模型(对应于分支的家谱结构)或“波动”模型来表示语言家族内的发散模式,从而形成(方言)连续体。然而,最近的系统发育分析倾向于将前者视为对于后者也是可行的理想化方法。但是对比很重要,因为对比通常反映了现实世界中的不同过程:说话者人口要么因迁移而分隔,要么在连续领土上扩展。由于历史经常在同一语言家族中留下两种模式的复杂性,因此理想情况下,我们需要一个模型来捕获这两种模式,并弄清每种模式各自的作用。系统发育方法的“网络”类型提供了此功能,因此我们回顾了语言数据的最新应用。大多数使用了词汇数据,这些数据被编码为二进制或多状态字符。相反,我们着眼于语音差异的连续距离测度。我们的输出网络以类似于已知历史的方式(类似于日耳曼语,尤其是英语)结合了分支和连续体状信号。因此,我们对传统上对共享创新的坚持提出了挑战,提出了一个新的,有原则的解释,说明尽管有共同的保留和并行创新,但从距离度量中可以正确地显示复杂的语言历史。

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