Word prediction is more than just predictability: An investigation of core vocabulary

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AX5ZRJGXL" target="_blank" >RIV/00216208:11320/25:X5ZRJGXL - isvavai.cz</a>

Výsledek na webu

<a href="https://escholarship.org/uc/item/8vb8s00h" target="_blank" >https://escholarship.org/uc/item/8vb8s00h</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Word prediction is more than just predictability: An investigation of core vocabulary

Popis výsledku v původním jazyce

What words are central in our semantic representations? In this experiment, we compared the core vocabulary derived from different association-based and language-based distributional models of semantic representation. Our question was: what kinds of words are easiest to guess given the surrounding sentential context? This task strongly resembles the prediction tasks on which distributional language models are trained, so core words from distributional models might be expected to be easier to guess. Results from 667 participants revealed that people's guesses were affected by word predictability, but that aspects of their performance could not be explained by distributional language models and were better captured by association-based semantic representations.

Název v anglickém jazyce

Word prediction is more than just predictability: An investigation of core vocabulary

Popis výsledku anglicky

What words are central in our semantic representations? In this experiment, we compared the core vocabulary derived from different association-based and language-based distributional models of semantic representation. Our question was: what kinds of words are easiest to guess given the surrounding sentential context? This task strongly resembles the prediction tasks on which distributional language models are trained, so core words from distributional models might be expected to be easier to guess. Results from 667 participants revealed that people's guesses were affected by word predictability, but that aspects of their performance could not be explained by distributional language models and were better captured by association-based semantic representations.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

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Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the Annual Meeting of the Cognitive Science Society

ISBN

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ISSN

1069-7977

e-ISSN

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Počet stran výsledku

7

Strana od-do

4106-4112

Název nakladatele

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Místo vydání

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Místo konání akce

Rotterdam, The Netherlands

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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