The statistical analysis of acoustic phonetic data: exploring differences between spoken Romance languages
Davide Pigoli, Pantelis Z. Hadjipantelis, John S. Coleman, John, A.D. Aston

TL;DR
This paper introduces a novel statistical method for analyzing acoustic phonetic data to explore language differences, using time-frequency representations and covariance modeling, demonstrated on Romance language recordings.
Contribution
It develops a new approach for modeling acoustic phonetic variation through covariance functions and phonetic transformations, enabling analysis of language differences from speech recordings.
Findings
Identified language-specific covariance functions in speech data.
Created a model to simulate how speakers sound in different languages.
Demonstrated the method on Romance language recordings of numbers.
Abstract
The historical and geographical spread from older to more modern languages has long been studied by examining textual changes and in terms of changes in phonetic transcriptions. However, it is more difficult to analyze language change from an acoustic point of view, although this is usually the dominant mode of transmission. We propose a novel analysis approach for acoustic phonetic data, where the aim will be to statistically model the acoustic properties of spoken words. We explore phonetic variation and change using a time-frequency representation, namely the log-spectrograms of speech recordings. We identify time and frequency covariance functions as a feature of the language; in contrast, mean spectrograms depend mostly on the particular word that has been uttered. We build models for the mean and covariances (taking into account the restrictions placed on the statistical analysis…
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