Cantonese natural language processing in the transformers era: a survey and current challenges

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A6473VWMP" target="_blank" >RIV/00216208:11320/25:6473VWMP - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11320/26:ZE8S8JJ4

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195564852&doi=10.1007%2fs10579-024-09744-w&partnerID=40&md5=6f20ec8c7b12c07ce19354001c9f794c" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195564852&doi=10.1007%2fs10579-024-09744-w&partnerID=40&md5=6f20ec8c7b12c07ce19354001c9f794c</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10579-024-09744-w" target="_blank" >10.1007/s10579-024-09744-w</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Cantonese natural language processing in the transformers era: a survey and current challenges

Popis výsledku v původním jazyce

Despite being spoken by a large population of speakers worldwide, Cantonese is under-resourced in terms of the data scale and diversity compared to other major languages. This limitation has excluded it from the current “pre-training and fine-tuning” paradigm that is dominated by Transformer architectures. In this paper, we provide a comprehensive review on the existing resources and methodologies for Cantonese Natural Language Processing, covering the recent progress in language understanding, text generation and development of language models. We finally discuss two aspects of the Cantonese language that could make it potentially challenging even for state-of-the-art architectures: colloquialism and multilinguality. © The Author(s) 2024.

Název v anglickém jazyce

Cantonese natural language processing in the transformers era: a survey and current challenges

Popis výsledku anglicky

Despite being spoken by a large population of speakers worldwide, Cantonese is under-resourced in terms of the data scale and diversity compared to other major languages. This limitation has excluded it from the current “pre-training and fine-tuning” paradigm that is dominated by Transformer architectures. In this paper, we provide a comprehensive review on the existing resources and methodologies for Cantonese Natural Language Processing, covering the recent progress in language understanding, text generation and development of language models. We finally discuss two aspects of the Cantonese language that could make it potentially challenging even for state-of-the-art architectures: colloquialism and multilinguality. © The Author(s) 2024.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

—

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

Language Resources and Evaluation

ISSN

1574-020X

e-ISSN

—

Svazek periodika

2024

Číslo periodika v rámci svazku

2024

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

27

Strana od-do

1-27

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85195564852