Phylogenetic signal in phonotactics
This provides a new source of data for historical and comparative linguistics, though it is incremental in extending phylogenetic methods to phonotactics.
The study tackled the problem of gaining historical insights from linguistic data by applying phylogenetic methods to statistical phonotactics from 111 Pama-Nyungan vocabularies, detecting phylogenetic signal in all datasets with greater signal in finer-grained and natural-class-based data.
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.