NLPHut's Participation at WAT2021
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10440569" target="_blank" >RIV/00216208:11320/21:10440569 - isvavai.cz</a>
Výsledek na webu
<a href="https://aclanthology.org/2021.wat-1.16.pdf" target="_blank" >https://aclanthology.org/2021.wat-1.16.pdf</a>
DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
NLPHut's Participation at WAT2021
Popis výsledku v původním jazyce
This paper provides the description of shared tasks to the WAT 2021 by our team "NLPHut". We have participated in the EnglishRIGHTWARDS ARROWHindi Multimodal translation task, EnglishRIGHTWARDS ARROWMalayalam Multimodal translation task, and Indic Multilingual translation task. We have used the state-of-the-art Transformer model with language tags in different settings for the translation task and proposed a novel "region-specific" caption generation approach using a combination of image CNN and LSTM for the Hindi and Malayalam image captioning. Our submission tops in EnglishRIGHTWARDS ARROWMalayalam Multimodal translation task (text-only translation, and Malayalam caption), and ranks secondbest in EnglishRIGHTWARDS ARROWHindi Multimodal translation task (text-only translation, and Hindi caption). Our submissions have also performed well in the Indic Multilingual translation tasks.
Název v anglickém jazyce
NLPHut's Participation at WAT2021
Popis výsledku anglicky
This paper provides the description of shared tasks to the WAT 2021 by our team "NLPHut". We have participated in the EnglishRIGHTWARDS ARROWHindi Multimodal translation task, EnglishRIGHTWARDS ARROWMalayalam Multimodal translation task, and Indic Multilingual translation task. We have used the state-of-the-art Transformer model with language tags in different settings for the translation task and proposed a novel "region-specific" caption generation approach using a combination of image CNN and LSTM for the Hindi and Malayalam image captioning. Our submission tops in EnglishRIGHTWARDS ARROWMalayalam Multimodal translation task (text-only translation, and Malayalam caption), and ranks secondbest in EnglishRIGHTWARDS ARROWHindi Multimodal translation task (text-only translation, and Hindi caption). Our submissions have also performed well in the Indic Multilingual translation tasks.
Klasifikace
Druh
O - Ostatní výsledky
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)
Návaznosti výsledku
Projekt
<a href="/cs/project/GX19-26934X" target="_blank" >GX19-26934X: Neuronové reprezentace v multimodálním a mnohojazyčném modelování</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2021
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů