Analyzing the Impact of Accent on English Speech: Acoustic and Articulatory Perspectives

TL;DR

This paper investigates how accents affect English speech by analyzing acoustic and articulatory features, proposing efficient methods to quantify accent strength, and providing insights for improving inclusive speech processing systems.

Contribution

It introduces a resource-efficient approach to quantify accent strength using eigenspectra and Vocal Tract Variables, advancing research on accented speech analysis.

Findings

Accented speech shows simpler coordination patterns and higher average pitch.

Proposed method effectively quantifies accent strength without extensive phonetic transcriptions.

Findings support development of more inclusive speech recognition systems.

Abstract

Advancements in AI-driven speech-based applications have transformed diverse industries ranging from healthcare to customer service. However, the increasing prevalence of non-native accented speech in global interactions poses significant challenges for speech-processing systems, which are often trained on datasets dominated by native speech. This study investigates accented English speech through articulatory and acoustic analysis, identifying simpler coordination patterns and higher average pitch than native speech. Using eigenspectra and Vocal Tract Variable-based coordination features, we establish an efficient method for quantifying accent strength without relying on resource-intensive phonetic transcriptions. Our findings provide a new avenue for research on the impacts of accents on speech intelligibility and offer insights for developing inclusive, robust speech processing systems that accommodate diverse linguistic communities.