Traditional dialectology or dialect geography is the study of geographical variation of language. Originated in Europe and pioneered in Germany and France, this field has predominantly been focusing on sounds, more specifically, on segments. Similarly, quantitative approaches to language variation concerned with the phonetic level are in most cases focusing on segments as well. However, more than half of the world’s languages include lexical tones (Yip, 2002). Despite this, tones are still underexplored in quantitative language comparison, partly due to the low accessibility of the suitable data. This paper aims to introduce a newly digitised dataset which comes from the Yue- and Pinghua-speaking areas in Southern China, with over 100 dialects. This dataset consists of two parts: tones and segments. In this paper, we illustrate how we can computationaly model tones in order to explore linguistic variation. We have applied a tone distance metric on our data, and we have found that 1) dialects also form a continuum on the tonal level and 2) other than tonemic (inventory) and tonetic differences, dialects can also differ in the lexical distribution of tones. The availability of this dataset will hopefully enable further exploration of the role of tones in quantitative typology and NLP research.

Recent studies suggested that language models are efficient tools for measuring lexical semantic change. In our paper, we present the compilation of the first graph-based evaluation dataset for lexical semantic change in the context of the Chinese language, specifically covering the periods of pre- and post- Reform and Opening Up. Exploiting the existing framework DURel, we collect over 61,000 human semantic relatedness judgments for 40 targets. The inferred word usage graphs and semantic change scores provide a basis for visualization and evaluation of semantic change.

In the last two decades, alignment analyses have become an important technique in quantitative historical linguistics and dialectology. Phonetic alignment plays a crucial role in the identification of regular sound correspondences and deeper genealogical relations between and within languages and language families. Surprisingly, up to today, there are no easily accessible benchmark data sets for phonetic alignment analyses. Here we present a publicly available database of manually edited phonetic alignments which can serve as a platform for testing and improving the performance of automatic alignment algorithms. The database consists of a great variety of alignments drawn from a large number of different sources. The data is arranged in a such way that typical problems encountered in phonetic alignment analyses (metathesis, diversity of phonetic sequences) are represented and can be directly tested.