Acoustic Cues to Automatic Identification of Phrase Boundaries in Lithuanian: A Preparatory Study

This study investigates whether specific acoustic features can reliably indicate phrase boundaries for automatic detection. It includes (1) an analysis of acoustic markers at the end of prosodic units—intonational phrases, intermediate phrases, and words—and (2) the evaluation of these features in an automatic boundary detection algorithm. Data were drawn from professionally and expressively read speech (893 words), news broadcasts (732 words), and interviews (361 words). Key features analyzed were pause duration, final sound lengthening, intensity, and F0 changes. Findings show that pauses and their duration are the most consistent indicators of phrase boundaries, especially at intonational phrase ends. Final sound lengthening and reductions in intensity and F0 also contribute but are less reliable for intermediate phrases. In automatic detection phonetic cues can be used to predict boundaries assigned by phoneticians 69% of the time. Read speech yielded better results than spontaneous speech. Among the features, pause presence and length were the most reliable, while F0 and intensity changes played a minor role.

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Publication Details

Journal
Languages
Published
2025-08-14
DOI
https://doi.org/10.3390/languages10080192
Primary Topic
Speech and dialogue systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Acoustic Cues to Automatic Identification of Phrase Boundaries in Lithuanian: A Preparatory Study

Asta Kazlauskienė, Gailius Raškinis, Eidmantė Kalašinskaitė-Zavišienė
Languages
Speech and dialogue systems
article

Acoustic Cues to Automatic Identification of Phrase Boundaries in Lithuanian: A Preparatory Study

Asta Kazlauskienė, Gailius Raškinis, Eidmantė Kalašinskaitė-Zavišienė
article en

Abstract

This study investigates whether specific acoustic features can reliably indicate phrase boundaries for automatic detection. It includes (1) an analysis of acoustic markers at the end of prosodic units—intonational phrases, intermediate phrases, and words—and (2) the evaluation of these features in an automatic boundary detection algorithm. Data were drawn from professionally and expressively read speech (893 words), news broadcasts (732 words), and interviews (361 words). Key features analyzed were pause duration, final sound lengthening, intensity, and F0 changes. Findings show that pauses and their duration are the most consistent indicators of phrase boundaries, especially at intonational phrase ends. Final sound lengthening and reductions in intensity and F0 also contribute but are less reliable for intermediate phrases. In automatic detection phonetic cues can be used to predict boundaries assigned by phoneticians 69% of the time. Read speech yielded better results than spontaneous speech. Among the features, pause presence and length were the most reliable, while F0 and intensity changes played a minor role.

LanguagesVol. 10(8)
Vytautas Magnus University (LT)
Openalex Percentile: Top 89%
Speech and dialogue systems
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