Beyond a Means to an End: A Case Study in Building Phonotactic Corpora for C entral A ustralian Languages (2025)

Abstract: Linguistic datasets are essential across fields: computational linguists use them for NLP development, theoretical linguists for statistical arguments supporting hypotheses about language, and documentary linguists for preserving examples and aiding grammatical descriptions. Transforming raw data (e.g., recordings or dictionaries) into structured forms (e.g., tables) requires non-trivial decisions within processing pipelines.This paper highlights the importance of these processes in understanding linguistic systems. Our contributions include: (1) an interactive dashboard for four central Australian languages with custom filters, and (2) demonstrating how data processing decisions influence measured outcomes.

## introduction with ubiquitous use of advanced nlp systems for language technology and linguistics (often by proxy), linguistic corpora and the processing it entails are often treated as a means to an end. in this paper, we show that the process is vital in enhancing our understanding of linguistic systems. each step in the processing pipeline embodies a linguistic decision that can be non-trivial. for example, when building a phonotactic corpus, we want each entry to be a root. but how do we judge what constitutes a root? should the decision be structural or semantic? the definition of how to classify a root has been a subject of numerous literature @xcite @xcite . to help guide this decision making we present an interactive web interface, to highlight the flow-on effects of analysis decisions. this system was designed with the following questions in mind: (1) are vowels distributed evenly across syllable positions? (2) does the vowel distribution by syllable position change across different parts of speech (pos)? (3) do some vowels occur more frequently in the root final position? (4) does the characteristic of the following consonant affect the distribution of vowels? (5) if the initial vowel is /a/, then what is the distribution of vowels in syllable 2; if the initial vowel is /i/, then what is the distribution of vowels in syllable 2; if the initial vowel is /u/, then what is the distribution of vowels in syllable 2? our contributions are two-fold; first, we present an interactive dashboard for four central australian languages with custom filter functions; second, we show that the processing of raw data into a desired format is embedded with decisions that alter the measured outcomes. the left-aligned side bar entails a settings control panel, starting with upload options, followed by options for language and filtering function to be applied. in the bottom half of the side bar, two analysis settings are presented: the vowel positions for vowel harmony, and the level of detail required for place of articulation distribution. the center console entails two tabs: 'tabular view' shows an interactive table of the data uploaded post-filtering, 'bar plot' shows the distribution of words with respect to word length (see figure 3 ). depicted beneath the console are four distributions calculated from the dataset: vowel distribution per syllable, root final vowel distribution, vowel harmony, and place of articulation distributions. (note: examples shown are made-up, for demonstration purposes only). the majority of corpus tools are built to examine word-level statistics, such as frequency or concordance. while it is possible to adapt these to analyse intra-word components, it can be intricate. addressing these concerns are often not possible with standard tools @xcite . @xcite advocates for diy tools, given their adaptability and efficiency to phenomena and corpus size. further, diy circumnavigate propriety software. in our design, we propose a local web-based inter-face to ensure data privacy and longevity. previous studies have presented online calculators for phonotactic distributions: english @xcite , modern standard arabic @xcite and czech @xcite . most of these resources appear to be hosted on external servers and some are no longer available. phonotactic structures in australian languages have been studied through the lenses of historical linguistics and typology (macklin-cordes and round, 2020, 2022), and it is advantageous for researchers to be able to bring insights from historical, areal and typological phenomena to inform analyses at different stages of the workflow. ## languages australian languages are characterised by small vowel inventories -often three distinctions in place and quality @xcite . over three quarters of australian languages have a vowel inventory between three and six vowels @xcite . consonant inventories exhibit elaborate place contrasts, but comparatively few manners of articulation @xcite . vowel harmony is observed more than 50% of the time across adjacent syllables in several australian languages @xcite . the phonetic inventories of the languages considered here are listed in kaytetye kaytetye (iso 639-3: gbb) is part of the arandic branch of the pama-nyungan family. it is primarily spoken in kaytetye country, which is approximately 300km north of alice springs (see figure 1 for approximate geographic region) @xcite . vowel inventory in kaytetye has been a subject of discussion, with accounts varying from two (/a/ and /@/) and four ([i], [a], [@], [u]) @xcite . in this paper we follow the four vowel analysis as we utilised the root corpus developed by @xcite foot_0 . pitjantjatjara pitjantjatjara (iso639-3: pjt) is a dialect of the western desert language @xcite and is a part of the pama-nyungan family. in 2016, over 3,000 speakers were recorded @xcite . it is closely related to the yankunytjatjara dialect @xcite . it follows the norm for australian languages, with a three vowel system and a consonant inventory that spans many places of articulation but fewer manners of articulation @xcite . warlpiri warlpiri (iso 639-3: wbp) is spoken in the northwest of alice springs by a few thousand people. it is a pama-nyungan language. it has one of the largest speaker populations of the australian languages @xcite . it aligns with the typical inventory of australian languages, featuring a three-vowel system and a consonant inventory with diverse articulation points but few articulation manners @xcite . warlpiri has been a subject of extensive study, particularly in the domain of syntax, given its free word order @xcite @xcite . warumungu warumungu (iso 639-3: wrm) is spoken by a few hundred people in the central part of the northern territory of australia around tennant creek. it is a member of the desert nyungic branch of the pama-nyungan family. it is closely related to warlpiri @xcite . the warumungu sound system is typical of australian languages. a three-way vowel system, five places of articulation and eight different possible manners of articulation. warumungu differs by having a second stop series. ## system a key consideration for this project is flexibility in working with the various forms of available data and different approaches to encoding similar phenomena. for example, one linguist might choose to encode a gloss field with additional notes, while another does not. corollary to this, custom filters and calculations can be added to the system. an additional consideration is privacy, given the non-public nature of some of these databases. for this reason, the system is designed to be run locally via a jupyter notebook on the operators computer. we use plotly dash module @xcite to generate an interactive dashboard foot_1 . ## conclusion we introduce a local web-based interactive dashboard designed for targeted analysis of phonotactic patterns, and illustrate its application to four central australian languages. this is a customizable tool which can be adapted for a variety of search and data conditioning tasks in a wide range of linguistic data, supporting interactive analyses of morpho-phonological phenomena. the toolkit works on the principle that an iterative interactive approach is required for robust linguisticallyinformed processing and analysis of complex and potentially inconsistent lexical datasets, especially in corpus composition decisions.