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Updated: Sep 13, 2025

Dissociation of the Confounding Influences of Expectancy and Integrative Difficulty Residing in Anomalous Sentences in Event-related Potential Studies

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Can Informativity Effects Be Predictability Effects in Disguise?

Vsevolod Kapatsinski¹

¹Department of Linguistics, University of Oregon, Eugene, OR 97403-1290, USA.

Entropy (Basel, Switzerland)

|July 29, 2025

Summary

This summary is machine-generated.

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Informativity, or information content, predicts speech reduction beyond local predictability. This study introduces a simulation method to distinguish genuine informativity effects from artifacts of predictability estimation in corpus linguistics.

Area of Science:

Corpus Linguistics
Phonetics
Psycholinguistics

Background:

Corpus linguistics shows informativity predicts articulatory reduction beyond local predictability.
Informativity is the inverse of average predictability, reflecting information content.
Existing research links informativity effects to speaker sensitivity to information or memory representations.

Purpose of the Study:

To propose a simulation method for estimating artifactual informativity effects.
To differentiate genuine informativity effects from those arising from improved predictability estimates.
To investigate the role of noise in predictability estimates within corpus data.

Main Methods:

Simulation-based approach to model informativity effects.

Keywords:

corpus linguistics informativity phonetics predictability reduction sound change usage-based linguistics

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Last Updated: Sep 13, 2025

Dissociation of the Confounding Influences of Expectancy and Integrative Difficulty Residing in Anomalous Sentences in Event-related Potential Studies

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Published on: May 9, 2019

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Estimating the proportion of the informativity effect attributable to predictability estimation.

Utilizing corpus probabilities as estimates for reduction behavior probabilities.

Main Results:

The proposed simulation can quantify the artifactual component of informativity effects.
It allows for the assessment of whether an observed informativity effect is likely genuine or an artifact.
The method helps determine the extent to which noise in predictability estimates influences observed effects.

Conclusions:

A novel simulation method is presented to disentangle genuine informativity effects from estimation artifacts in corpus linguistics.
This approach provides a framework for robustly investigating the role of informativity in articulatory reduction.
The findings contribute to a more accurate understanding of how information content influences speech production.