Multimodal Machine Translation Approaches for Indian Languages: A Comprehensive Survey

Kód výsledku v IS VaVaI

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

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195373878&doi=10.3897%2fjucs.109227&partnerID=40&md5=b97bbc8ac7d695af8ecf11125324cc72" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195373878&doi=10.3897%2fjucs.109227&partnerID=40&md5=b97bbc8ac7d695af8ecf11125324cc72</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3897/jucs.109227" target="_blank" >10.3897/jucs.109227</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multimodal Machine Translation Approaches for Indian Languages: A Comprehensive Survey

Popis výsledku v původním jazyce

Multimodal machine translation (MMT) is a challenging task in the linguistically diverse Indian landscape. Machine translation refers to the task of automatically converting content from one language to another without human involvement. Within the realm of natural language processing, a significant challenge arises from the inherent ambiguity present in human language. Translation ambiguity is a cross-lingual phenomenon that can manifest itself for various reasons, including lexical ambiguity, the occasional need to impute missing words, the presence of gender ambiguity, and word-sense ambiguities. These factors can lead to a decrease in translation accuracy. The integration of multiple modalities, such as images, videos, and audio, in addition to text, plays a pivotal role in improving the robustness and precision of translation systems. Over the past five years, extensive research has been dedicated to incorporating secondary modalities alongside text to improve language translation and comprehension. In this comprehensive study, our objective was to identify and explore promising MMT approaches, available corpora, evaluation metrics, research challenges, and the future direction of research specifically for Indian languages. We evaluated 81 papers, including MMT models, MMT dataset in Indian languages, survey on MMT approach, and the effects of multiple modalities in machine translation. The performance of the different proposed approaches has also been briefly analyzed on the basis of the claimed results and comparative evaluations. Finally, the challenges associated with the MMT task for India and some possible directions for future research in this domain are highlighted. © 2024, IICM. All rights reserved.

Název v anglickém jazyce

Multimodal Machine Translation Approaches for Indian Languages: A Comprehensive Survey

Popis výsledku anglicky

Multimodal machine translation (MMT) is a challenging task in the linguistically diverse Indian landscape. Machine translation refers to the task of automatically converting content from one language to another without human involvement. Within the realm of natural language processing, a significant challenge arises from the inherent ambiguity present in human language. Translation ambiguity is a cross-lingual phenomenon that can manifest itself for various reasons, including lexical ambiguity, the occasional need to impute missing words, the presence of gender ambiguity, and word-sense ambiguities. These factors can lead to a decrease in translation accuracy. The integration of multiple modalities, such as images, videos, and audio, in addition to text, plays a pivotal role in improving the robustness and precision of translation systems. Over the past five years, extensive research has been dedicated to incorporating secondary modalities alongside text to improve language translation and comprehension. In this comprehensive study, our objective was to identify and explore promising MMT approaches, available corpora, evaluation metrics, research challenges, and the future direction of research specifically for Indian languages. We evaluated 81 papers, including MMT models, MMT dataset in Indian languages, survey on MMT approach, and the effects of multiple modalities in machine translation. The performance of the different proposed approaches has also been briefly analyzed on the basis of the claimed results and comparative evaluations. Finally, the challenges associated with the MMT task for India and some possible directions for future research in this domain are highlighted. © 2024, IICM. All rights reserved.

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

Journal of Universal Computer Science

ISSN

0948-695X

e-ISSN

—

Svazek periodika

30

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

24

Strana od-do

694-717

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85195373878