Predicting mutual intelligibility in Chinese dialects

ABSTRACT We determined mutual intelligibility and linguistic similarity by presenting recordings of the same fable spoken in 15 Chinese dialects to naive listeners of the same set of dialects and asking them to rate the dialects along both subjective dimensions. We then regressed the ratings against objective structural measures (lexical similarity, phonological correspondence) for the same set of dialects. Our results show that subjective similari ty is better predicted than subjective mutual intelligibility and that the relationship between objective and subjective measures is logarithmic. Best predicted was log-transformed subjective similarity with R 2 = . 64 . Keywords: Dialectology, dialectometry, linguistic distance, (mutual) intelligibility, perceptual rati ng. 1. INTRODUCTION 1.1. Why study mutual intelligibility? Distance between languages is used as a criterion when arguing about genealogical relationships between languages. The more the languages re-semble each other, the more likely they are derived from the same parent language, i.e., belong to the same language family. However, it is difficult to quantify the distance between languages one-dimensionally since languages differ along many structural dimensions (e.g. phonetics, phonology, morphology, syntax). It is unclear how the various dimensions should be weighed against each other. Therefore, we select a single criterion mutual intelligibility. Mutual intelligibility is an overa ll criterion that may tell us whether two languages are similar/ close. Useful work on structural measures of differ-ence between related languages has been done, for instance, at Stanford University (for Gaelic Irish dialects, cf. [1]) and at the University of Groning en (for Dutch [2] and Norwegian dialects [3]), using the Levenshtein distance. This is a similarity metric that computes the mean number of string operations needed to convert a word in one language to its counterpart in the other language. This measure was then used to build a tree structure (through hierarchical cluster analysis) which matched the language family tree as con-structed by linguists. 1.2. How to determine (mutual) intelligibility? Although methods for determining intelligibility are well-established, for instance in the fields of speech technology and audiology, the practical problems are prohibitive when mutual intelligibi-lity has to be established for, say, all pairs of varieties in a set of 15 dialects (yielding 225 pai rs). Rather than measuring intelligibility by functional tests, opinion testing has been advanced as a short -cut. That is, the indices of the measurements of mutual intelligibility between languages are gener-ated from listeners judgment scores. Once mutual intelligibility scores are available, the relative predictive power of structural dimensions can be found through regression analysis. Such work has recently been done for 15 Norwegian dialects by Gooskens and Heeringa [3] (henceforth G&H). Their results show that subjectively judged dis-tance between sample dialects and the listeners own dialect correlated substantially with the ob-jective Levenshtein distance ( r