Modeling the predictive potential of extralinguistic context with script knowledge: The case of fragments.

We describe a novel approach to estimating the predictability of utterances given extralinguistic context in psycholinguistic research. Predictability effects on language production and comprehension are widely attested, but so far predictability has mostly been manipulated through local linguistic...

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Main Authors: Robin Lemke, Lisa Schäfer, Ingo Reich
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0246255
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spelling doaj-85c66082084d41d6acd7c6fdf3be834b2021-07-30T04:30:54ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01162e024625510.1371/journal.pone.0246255Modeling the predictive potential of extralinguistic context with script knowledge: The case of fragments.Robin LemkeLisa SchäferIngo ReichWe describe a novel approach to estimating the predictability of utterances given extralinguistic context in psycholinguistic research. Predictability effects on language production and comprehension are widely attested, but so far predictability has mostly been manipulated through local linguistic context, which is captured with n-gram language models. However, this method does not allow to investigate predictability effects driven by extralinguistic context. Modeling effects of extralinguistic context is particularly relevant to discourse-initial expressions, which can be predictable even if they lack linguistic context at all. We propose to use script knowledge as an approximation to extralinguistic context. Since the application of script knowledge involves the generation of prediction about upcoming events, we expect that scrips can be used to manipulate the likelihood of linguistic expressions referring to these events. Previous research has shown that script-based discourse expectations modulate the likelihood of linguistic expressions, but script knowledge has often been operationalized with stimuli which were based on researchers' intuitions and/or expensive production and norming studies. We propose to quantify the likelihood of an utterance based on the probability of the event to which it refers. This probability is calculated with event language models trained on a script knowledge corpus and modulated with probabilistic event chains extracted from the corpus. We use the DeScript corpus of script knowledge to obtain empirically founded estimates of the likelihood of an event to occur in context without having to resort to expensive pre-tests of the stimuli. We exemplify our method at a case study on the usage of nonsentential expressions (fragments), which shows that utterances that are predictable given script-based extralinguistic context are more likely to be reduced.https://doi.org/10.1371/journal.pone.0246255
collection DOAJ
language English
format Article
sources DOAJ
author Robin Lemke
Lisa Schäfer
Ingo Reich
spellingShingle Robin Lemke
Lisa Schäfer
Ingo Reich
Modeling the predictive potential of extralinguistic context with script knowledge: The case of fragments.
PLoS ONE
author_facet Robin Lemke
Lisa Schäfer
Ingo Reich
author_sort Robin Lemke
title Modeling the predictive potential of extralinguistic context with script knowledge: The case of fragments.
title_short Modeling the predictive potential of extralinguistic context with script knowledge: The case of fragments.
title_full Modeling the predictive potential of extralinguistic context with script knowledge: The case of fragments.
title_fullStr Modeling the predictive potential of extralinguistic context with script knowledge: The case of fragments.
title_full_unstemmed Modeling the predictive potential of extralinguistic context with script knowledge: The case of fragments.
title_sort modeling the predictive potential of extralinguistic context with script knowledge: the case of fragments.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2021-01-01
description We describe a novel approach to estimating the predictability of utterances given extralinguistic context in psycholinguistic research. Predictability effects on language production and comprehension are widely attested, but so far predictability has mostly been manipulated through local linguistic context, which is captured with n-gram language models. However, this method does not allow to investigate predictability effects driven by extralinguistic context. Modeling effects of extralinguistic context is particularly relevant to discourse-initial expressions, which can be predictable even if they lack linguistic context at all. We propose to use script knowledge as an approximation to extralinguistic context. Since the application of script knowledge involves the generation of prediction about upcoming events, we expect that scrips can be used to manipulate the likelihood of linguistic expressions referring to these events. Previous research has shown that script-based discourse expectations modulate the likelihood of linguistic expressions, but script knowledge has often been operationalized with stimuli which were based on researchers' intuitions and/or expensive production and norming studies. We propose to quantify the likelihood of an utterance based on the probability of the event to which it refers. This probability is calculated with event language models trained on a script knowledge corpus and modulated with probabilistic event chains extracted from the corpus. We use the DeScript corpus of script knowledge to obtain empirically founded estimates of the likelihood of an event to occur in context without having to resort to expensive pre-tests of the stimuli. We exemplify our method at a case study on the usage of nonsentential expressions (fragments), which shows that utterances that are predictable given script-based extralinguistic context are more likely to be reduced.
url https://doi.org/10.1371/journal.pone.0246255
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