Source-linked AI summary
Acoustic gap placement in second-language read speech production
Peyman Jahanbin
TL;DR
Global pause totals do not show whether interruptions occur at comparable linguistic locations, even though placement is a dimension of breakdown fluency. This study compares aligned interword gaps at punctuation-marked and unpunctuated positions in a fixed read passage. The groups differed primarily at unpunctuated positions, and the findings support placement-sensitive measurement within fixed-passage read speech.
Problem
Global pause counts do not reveal whether interruptions occupy comparable linguistic locations, although placement is an important property of breakdown fluency.
Source: Introduction · p. 3Method
The study used word-level forced alignment to extract interword acoustic gaps and compared their placement across punctuation-marked and unpunctuated positions in a fixed passage.
Source: Forced alignment and gap extraction · p. 8Results
The Mandarin and American English groups differed primarily in gap frequency and cumulative duration at unpunctuated positions, rather than at punctuation-marked boundaries.
Source: Conclusion · p. 22Takeaways & Limitations
The findings support acoustic gap placement as a reproducible observable dimension of breakdown fluency in fixed-passage read speech.
Source: Conclusion · p. 22The study does not establish the cause of the group association or a proficiency or perceptual consequence.
Source: Discussion · p. 21, Conclusion · p. 22
Abstract
from arXiv · showhide
Speakers can differ not only in how much silence they produce but also in where interruptions fall, information that global pause counts obscure. We analyzed 115 publicly available Speech Accent Archive recordings of the same read passage: 57 speakers whose archive metadata listed Mandarin as their first language and a mainland-China birthplace, and 58 American English first-language speakers born in the U.S. Midwest. Word-level forced alignment was used to extract interword acoustic gaps and classify each position as punctuation-marked or unpunctuated. At a 250 ms threshold, punctuation-marked gaps were similar for the Mandarin and English groups (means 5.56 and 5.47), whereas unpunctuated-position gaps were more frequent in the Mandarin group (means 3.67 and 0.43; adjusted rate ratio 11.98, 95% confidence interval 6.53-22.00). A crossed-effects logistic model with random intercepts for speakers and passage positions confirmed that the contrast was disproportionately concentrated at unpunctuated positions (interaction odds ratio 9.44, 95% confidence interval 5.23-17.02). The pattern persisted at a 500 ms threshold, after removing positions adjacent to punctuation, after excluding severe transcript-deviation cases, and when analysis was restricted to acoustically confirmed silence. Nearly half of the Mandarin group's unpunctuated gaps occurred at positions classified as within-phrase in an exploratory single-coder annotation. In this fixed-passage corpus, acoustic gap placement relative to textual and syntactic structure distinguished the groups more clearly than punctuation-marked pausing. The results support placement-sensitive measurement as a reproducible dimension of breakdown fluency while not establishing a causal mechanism, proficiency difference, or perceptual consequence.
Introduction
Global pause counts capture how much interruption occurs but not where it falls, although pause location can distinguish performances and matters to listeners. This study compares punctuation-marked and unpunctuated gaps across speakers reading the same passage, testing whether group differences depend on placement.
Motivation
- A global count can assign the same value to speakers whose gaps fall at different linguistic locations, obscuring differences in interruption placement.Prior work indicates that pause location can differentiate learner and first-language speech and that listeners respond to where pauses occur.Source: Introduction · p. 3
Related work
- Prior research found group differences within utterances but not at utterance boundaries, showing that pause contrasts can depend on location.Other work relates pauses to boundary level, syntactic complexity, and comprehensibility.Source: Introduction · pp. 3–4
Study setting
- Reading holds lexical content and word order constant across speakers, while punctuation provides a reproducible but incomplete indicator of textual boundaries.Unlike spontaneous speech, a fixed passage limits variation from content selection, formulation, retrieval, repair, and interaction; findings from one passage may not generalize to spontaneous speech or other texts.Source: Introduction · p. 4
Analytical approach
- The analysis uses 250 ms as its primary gap threshold and 500 ms as a stricter sensitivity threshold, alongside an acoustic criterion because aligned intervals are not necessarily silent pauses.The study contrasts every punctuation-marked boundary with every unpunctuated position rather than selecting likely pause sites.Source: Introduction · pp. 4–5
Research questions
- The study asks whether group differences in gap counts and durations vary by punctuation status, survive robustness checks, and extend to exploratory within-phrase positions.The syntactic refinement is exploratory, and gap locations are not treated as direct evidence of a cognitive mechanism.Source: Introduction · p. 5
Materials and methods
The methods use a fixed read passage and word-level alignment to compare gap placement across two archive-defined speaker groups. Position-level and speaker-level analyses, supplemented by sensitivity checks, test the placement contrast while treating the syntactic refinement as exploratory.
Corpus, participant selection, and sample size
- The analytic sample contained 115 speakers: 57 Mandarin first-language speakers born in mainland China and 58 American English first-language speakers born in the Midwest.Three Mandarin-labeled records that did not meet the mainland-China birthplace rule were excluded before any model was fit.Source: Corpus, participant selection, and… · p. 6
Ethics and privacy
- The study used pre-existing public archive recordings and metadata, with no participant interaction or access to private information.The article does not redistribute audio; supporting files include public archive codes and URLs plus derived timing variables and analysis outputs.Source: Ethics and privacy · p. 7
Passage and boundary map
- The 69-word passage had 68 interword positions: three sentence-final and four punctuation-internal positions formed seven punctuation-marked boundaries, while the remaining 61 positions were unpunctuated.Because every speaker read the same word sequence, these denominators were constant across participants. Punctuation indicated visible textual boundary marking, not a complete syntactic or prosodic analysis.Source: Passage and boundary map · p. 7
Forced alignment and gap extraction
- Word-level forced alignment yielded interword intervals calculated from adjacent aligned word boundaries, with positive intervals retained as acoustic gaps.Gaps of at least 250 ms were counted in the primary analysis and at least 500 ms in the stricter analysis; positive aligned intervals were not assumed to be manually verified silence.Source: Forced alignment and gap extraction · p. 8
Statistical analysis
- The primary inferential test was a crossed-effects logistic model of gap occurrence at 68 positions per speaker, with random intercepts for speakers and passage positions.The focal group-by-unpunctuated interaction tested whether the group contrast was larger at unpunctuated positions; count, duration, and opportunity models provided complementary analyses.Source: Statistical analysis · pp. 9–10
Quality control and sensitivity analyses
- Sensitivity checks examined a 500 ms threshold, punctuation-adjacent positions, transcript deviations, and acoustically confirmed silence.Manual inspection distinguished audible gaps from precise word-boundary placement; the transcript screen was auxiliary, and the silence criterion was independent of the aligner’s interval classification although interval boundaries came from alignment.Source: Quality control and sensitivity analyses · pp. 11–12
Use of artificial intelligence tools
- AI tools assisted with manuscript preparation and verification tasks, while the author verified archive records, reviewed code, reran analyses, and approved the content.The tools did not generate or alter recordings or derived measurements, define eligibility or outcomes, or select statistical conclusions.Source: Use of artificial intelligence tools · p. 12
Results
Across the fixed-passage recordings, the Mandarin–English contrast was concentrated at unpunctuated positions rather than punctuation-marked positions. That placement-specific pattern persisted across model and robustness checks, while nearly half of Mandarin speakers’ unpunctuated gaps were classified as within-phrase.
Alignment and sample quality
- The sample comprised 57 Mandarin and 58 American English speakers; all 115 alignments matched the expected 69-word sequence, with no negative interword gaps detected.With voice-activity detection, 99 recordings were classified as clean, 14 as minor or moderate deviations, and two as severe mismatches.Source: Alignment and sample quality · pp. 12–13
Descriptive placement results
- At 250 ms, punctuation-marked means were 5.56 for Mandarin and 5.47 for English speakers, while unpunctuated means were 3.67 and 0.43, respectively.The figure maps gaps across 68 interword positions and summarizes speaker-level unpunctuated counts.Source: Descriptive placement results · p. 13, Figure 1 · p. 14, Table 3 · p. 14
Robustness and acoustic validation
- At 500 ms, unpunctuated means remained higher for Mandarin than English speakers (1.54 versus 0.09); removing positions adjacent to punctuation also retained the contrast at both thresholds.For nonadjacent positions, 250 ms means were 3.21 versus 0.36, and 500 ms means were 1.25 versus 0.09.Source: Descriptive placement results · p. 14, Robustness and acoustic validation · p. 16
Primary models
- The crossed-effects interaction odds ratio was 9.44 (95% CI 5.23–17.02); the adjusted unpunctuated-gap rate ratio was 11.98 (95% CI 6.53–22.00), versus 1.03 for punctuation-marked gaps.The punctuation-marked contrast was nonsignificant; the position-level model accounted for speaker and position heterogeneity.Source: Primary models · p. 15, Table 4 · p. 15
Robustness and acoustic validation
- Restricting analysis to independently confirmed silence preserved the unpunctuated count effect (rate ratio 11.30, 95% CI 5.78–22.11); excluding four severe transcript cases also retained the contrast.All nine manually inspected intervals were audible gaps, though three had imperfect TextGrid word-boundary placement.Source: Robustness and acoustic validation · pp. 16–17
Syntactic placement
- Of 209 Mandarin unpunctuated gaps, 101 (48.3%) were at positions classified as within-phrase; within-phrase means were 1.77 gaps per Mandarin speaker and 0.07 per English speaker.The exploratory result is qualified by the English floor and a single-coder, rule-based annotation.Source: Syntactic placement · p. 17
Discussion
The group contrast in this fixed-passage corpus was concentrated at unpunctuated positions rather than punctuation-marked ones, and it persisted across complementary analyses. The discussion presents placement-sensitive measurement as information that global totals discard, while limiting interpretation to the observed recordings and measures.
Discussion
- Placement-sensitive measures retain information that global pause totals discard, since different distributions across a text can yield the same total.In this corpus, the total-count rate ratio of 1.67 combined a punctuation-marked rate ratio near one with an unpunctuated rate ratio of 11.98.Source: Discussion · p. 18
- Unpunctuated gaps had a rate ratio of 11.98, while punctuation-marked rates were near one; duration models led to the same conclusion.The crossed-effects interaction accounted for speaker and passage-position variation, and the focal contrast persisted in sensitivity analyses, including models restricted to acoustically confirmed silence.Source: Discussion · pp. 18, 20
- The full-passage contrast extends selected-boundary analyses by showing that the strongest group contrast occurred away from visible punctuation, not by contradicting them.The discussion characterizes this as broader analytic coverage: selected-boundary and full-passage analyses address different questions.Source: Discussion · p. 19
- Forced-alignment-based gaps were not treated as manually verified pauses, but the aggregate contrast survived an independent acoustic criterion.Manual inspection found audible gaps in inspected intervals while also noting possible word-boundary placement errors; the acoustic criterion confirmed most counted events.Source: Discussion · pp. 19–20
- Nearly half of the Mandarin group’s unpunctuated gaps were classified as within-phrase, but the English distribution was near a floor and the comparison is statistically unstable as a general quantity.The binary syntactic refinement was assigned by one coder and does not represent graded syntactic distance or prosodic constituency.Source: Discussion · p. 20
- The findings characterize a purposive sample of 115 recordings reading one passage, not population prevalence or spontaneous-speech performance.The study also cannot identify a causal mechanism, establish a general syntactic-processing difference, or determine effects on perceived fluency or comprehensibility.Source: Discussion · pp. 19–21
Conclusion
In this fixed-passage archival corpus, the groups differed primarily in unpunctuated interword gaps, and the contrast persisted across several checks. The findings support acoustic gap placement as a reproducible dimension of breakdown fluency, without establishing its cause or a proficiency or perceptual consequence.
Conclusion
- The groups differed primarily in the frequency and cumulative duration of interword acoustic gaps at unpunctuated positions, not punctuation-marked boundaries.This result is scoped to a fixed-passage archival corpus.Source: Conclusion · p. 22
- The placement contrast persisted at a stricter duration threshold, after excluding punctuation-adjacent positions and severe transcript deviations, and when analysis was restricted to acoustically confirmed silence.Source: Conclusion · p. 22
- Nearly half of the Mandarin group's unpunctuated gaps fell at positions classified as within-phrase, but the exploratory result was limited by a single coder and an English floor.Source: Conclusion · p. 22
- The findings support acoustic gap placement as a reproducible dimension of breakdown fluency, but do not establish a causal mechanism, proficiency difference, or perceptual consequence.Source: Conclusion · p. 22
Data availability
The original recordings and public metadata are available from the Speech Accent Archive, while the article provides derived data and materials needed to reproduce the findings.
Data availability
- Original recordings and public metadata are available from the Speech Accent Archive, but the article does not redistribute audio.Source: Data availability · p. 22
- S2 Data and S3 File provide derived participant- and gap-level data, annotations, model inputs and outputs, and analysis code for reproducing the findings.Source: Data availability · p. 23
- If accepted, the S3 reproducibility package will also be deposited in the Open Science Framework, with its DOI and URL added before publication.Source: Data availability · p. 23
Supporting information captions
The supporting information comprises an appendix of methods and statistical materials, participant metadata and selection audit, and a reproducibility package.
Supporting information captions
- S1 Appendix contains supporting methods, quality-control results, and full statistical tables.Source: Supporting information captions · p. 27
- S2 Data contains participant metadata, the selection audit, and source URLs for the final analytic sample.Source: Supporting information captions · p. 27
- S3 File contains derived gap-level data, boundary annotations, model inputs and outputs, R code, a data dictionary, and a README.Source: Supporting information captions · p. 27