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Related Experiment Video

Updated: Mar 9, 2026

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

Seeking Temporal Predictability in Speech: Comparing Statistical Approaches on 18 World Languages.

Yannick Jadoul¹, Andrea Ravignani¹, Bill Thompson¹

¹Artificial Intelligence Lab, Vrije Universiteit Brussel Brussels, Belgium.

Frontiers in Human Neuroscience

|December 21, 2016

Summary

Speech timing predictability aids language acquisition by providing clues for segmenting speech. This study found limited evidence for temporal predictability across 18 languages, suggesting it arises from multiple weak cues.

Keywords:

Bayesian autoregressive models nPVI rhythm speech perception temporal structure time series timing

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Last Updated: Mar 9, 2026

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Published on: September 27, 2024

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

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Published on: August 9, 2024

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

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Published on: October 13, 2018

Area of Science:

Speech perception and language acquisition
Computational linguistics
Phonetics and acoustics

Background:

Temporal regularities in speech are hypothesized to aid early language acquisition by providing cues for speech segmentation.
Existing measures of speech timing focus on adjacent units and are sensitive to data idiosyncrasies.

Purpose of the Study:

To investigate the predictability of syllable occurrence across 18 languages using acoustic measures.
To test whether higher-order temporal structures contribute to perceived speech regularities.
To identify cross-linguistic temporal predictability exploitable by language learners.

Main Methods:

Analysis of distributional regularities using Bayesian ideal learner and simple distributional measures.
Modeling of higher-order temporal structures in syllable timing series.
Comparison of statistical methods across acoustic, not orthographic, measures.

Main Results:

Limited evidence for temporal predictability at various time scales was found across the analyzed languages.
Higher-order temporal predictability in speech timing was difficult to reliably infer.
The study suggests predictability may stem from a combination of weak perceptual cues at multiple levels.

Conclusions:

Temporal predictability in speech is challenging to pinpoint using current objective measures.
Learners may exploit a combination of subtle temporal cues across different structural levels.
Further research is needed to fully understand the role of temporal structure in speech acquisition.