Acoustic Cues to Automatic Identification of Phrase Boundaries in Lithuanian: A Preparatory Study
Year: 2025
Type: article
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.
Source: Languages
Institution: Vytautas Magnus University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,689
OpenAlex ID: W4413416682