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14 - Evaluating Three Advanced Methods for Sociophonetic Studies

Whisper, LaBB-CAT and PrInDT

from Section 3 - Corpus-Based Research on Variable Usage in Place and Medium

Published online by Cambridge University Press:  25 June 2026

Adam Smith
Affiliation:
Macquarie University, Sydney
Peter Collins
Affiliation:
University of New South Wales, Sydney
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Summary

Since the early 2000s, various methods for analysing speech data have emerged. While several publications offer strong overviews of methodological innovations, most of them reflect the state of research from over a decade ago. Recent advances in speech technology and statistics relevant to sociophonetic studies have rarely been addressed. This chapter aims to provide an up-to-date overview of three advanced methods for investigating sociophonetic variation, covering both data preparation and analysis, illustrated with a case study on spoken Scottish English. For data preparation, the chapter shows how OpenAI Whisper, an automatic speech recognition model, can transcribe speech and produce outputs compatible with linguistic software. It also discusses how speech annotation tasks can be improved via LaBB-CAT, a tool for corpus management and data mining. For data analysis, the chapter outlines how sociophonetic studies can benefit from advanced statistical methods, including regression and decision tree modelling as well as model evaluation. A key example is the PrInDT package, developed to optimise conditional inference trees as well as classification and regression tasks.

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