论文标题
系统发育信号
Phylogenetic signal in phonotactics
论文作者
论文摘要
系统发育方法在树推断以外的语言学中具有广泛的潜力。在这里，我们展示了系统发育方法如何打开从全新的语言数据中获得历史见解的可能性 - 在这种情况下，统计语音学。我们从111个PAMA-NYUNGAN词汇中提取音效数据，并应用系统发育信号的测试，量化数据反映系统发育病史的程度。我们测试了三个数据集：（1）二进制变量记录了在词典中（2）段之间的过渡频率和（3）天然声音类之间过渡的频率的二进制变量（两段序列）（2）。澳大利亚语言的特征是具有高度的语音同质性。然而，我们在所有数据集中都检测到系统发育信号。系统发育频率数据的系统发育信号比二元数据更大，并且基于天然一流的数据最大。这些结果表明，在历史和比较语言学中采用新的可提取数据来源的可行性。
Phylogenetic methods have broad potential in linguistics beyond tree inference. Here, we show how a phylogenetic approach opens the possibility of gaining historical insights from entirely new kinds of linguistic data--in this instance, statistical phonotactics. We extract phonotactic data from 111 Pama-Nyungan vocabularies and apply tests for phylogenetic signal, quantifying the degree to which the data reflect phylogenetic history. We test three datasets: (1) binary variables recording the presence or absence of biphones (two-segment sequences) in a lexicon (2) frequencies of transitions between segments, and (3) frequencies of transitions between natural sound classes. Australian languages have been characterized as having a high degree of phonotactic homogeneity. Nevertheless, we detect phylogenetic signal in all datasets. Phylogenetic signal is greater in finer-grained frequency data than in binary data, and greatest in natural-class-based data. These results demonstrate the viability of employing a new source of readily extractable data in historical and comparative linguistics.
