@article{sward-etal-2026-much,
    title = "How Much Data for Stable Formant Values? Pipeline for Convergence Detection Based on Read Speech",
    author = "Sward, Kayla  and
      Sjons, Johan  and
      Ekstrom, Axel G.",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    journal = "International Conference on Language Resources and Evaluation",
    volume = "main",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://preview.aclanthology.org/ingest-lrec/2026.lrec-main.470/",
    pages = "5916--5925",
    abstract = "This study investigates the stability and convergence of vowel formants (F1, F2, F3) in read speech through an extensive corpus of audiobook recordings. While most formant studies rely on brief, isolated utterances recorded in laboratory settings, this analysis draws on 3,384 chapters (about 942 hours) of continuous, stylistically varied speech from publicly available audiobooks. The data was processed using an automated pipeline that comprised transcription, phoneme alignment, and formant extraction. Several statistical techniques {--} First Token Within (FTW), Cumulative Sum (CUSUM), Two-Sample t-Test, Confidence Interval (CI) Shrinkage, Piecewise Linear Fitting (PWLF), and Binary Segmentation (BinSeg) {--} were compared for their effectiveness in identifying stabilization points. Findings indicate that formant means generally stabilize within 60 to 230 vowel tokens per phoneme, dependent on vowel type and speaker gender. Of the methods that were evaluated, CUSUM yielded the most consistent and informative results. The results provide practical guidelines for determining the quantity of non-laboratory speech required to obtain reliable vowel formant averages."
}