Is it Possible to Re-educate RoBERTa? Expert-driven Machine Learning for Punctuation Correction.

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F23%3A43969896" target="_blank" >RIV/49777513:23520/23:43969896 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216224:14210/23:00131927

Výsledek na webu

<a href="https://doi.org/10.2478/jazcas-2023-0052" target="_blank" >https://doi.org/10.2478/jazcas-2023-0052</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2478/jazcas-2023-0052" target="_blank" >10.2478/jazcas-2023-0052</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Is it Possible to Re-educate RoBERTa? Expert-driven Machine Learning for Punctuation Correction.

Popis výsledku v původním jazyce

Although Czech rule-based tools for automatic punctuation insertion rely on extensive grammar and achieve respectable precision, the pre-trained Transformers outperform rule-based systems in precision and recall (Machura et al. 2022). The Czech pre-trained RoBERTa model achieves excellent results, yet a certain level of phenomena is ignored, and the model partially makes errors. This paper aims to investigate whether it ispossible to retrain the RoBERTa language model to increase the number of sentence commas the model correctly detects. We have chosen a very specific and narrow type of sentence comma, namely the sentence comma delimiting vocative phrases, which is clearly defined in the grammar and is very often omitted by writers. The chosen approaches were further tested and evaluated on different types of texts.

Název v anglickém jazyce

Is it Possible to Re-educate RoBERTa? Expert-driven Machine Learning for Punctuation Correction.

Popis výsledku anglicky

Although Czech rule-based tools for automatic punctuation insertion rely on extensive grammar and achieve respectable precision, the pre-trained Transformers outperform rule-based systems in precision and recall (Machura et al. 2022). The Czech pre-trained RoBERTa model achieves excellent results, yet a certain level of phenomena is ignored, and the model partially makes errors. This paper aims to investigate whether it ispossible to retrain the RoBERTa language model to increase the number of sentence commas the model correctly detects. We have chosen a very specific and narrow type of sentence comma, namely the sentence comma delimiting vocative phrases, which is clearly defined in the grammar and is very often omitted by writers. The chosen approaches were further tested and evaluated on different types of texts.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/GA22-27800S" target="_blank" >GA22-27800S: Využití vícemodálních Transformerů pro přirozenější hlasový dialog</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Journal of Linguistics

ISSN

0021-5597

e-ISSN

1338-4287

Svazek periodika

74

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

PL - Polská republika

Počet stran výsledku

12

Strana od-do

357-368

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85181757325