CONF
Parida_WAT2021_2021/IDIAP
NLPHut's Participation at WAT2021
Parida, Shantipriya
Panda, Subhadarshi
Kotwal, Ketan
Dash, Amulya Ratna
Dash, Satya Ranjan
Sharma, Yashvardhan
Motlicek, Petr
Bojar, Ondrej
EXTERNAL
https://publications.idiap.ch/attachments/papers/2021/Parida_WAT2021_2021.pdf
PUBLIC
https://publications.idiap.ch/index.php/publications/showcite/Parida_Idiap-RR-10-2021
Related documents
Proceedings of the 8th Workshop on Asian Translation (WAT2021)
2021
Association for Computational Linguistics
146--154
978-1-954085-63-3
https://aclanthology.org/2021.wat-1.16/
URL
This paper provides the description of shared tasks to the WAT 2021 by our team NLPHut's. We have participated in the English→Hindi Multimodal translation task, English→Malayalam Multimodal translation task, and Indic Multi-lingual 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 English→Malayalam Multimodal translation task (text-only translation, and Malayalam caption), and ranks second-best in English→Hindi Multimodal translation task (text-only translation, and Hindi caption). Our submissions have also performed well in the Indic Multilingual translation tasks.
REPORT
Parida_Idiap-RR-10-2021/IDIAP
NLPHut?s Participation at WAT2021
Parida, Shantipriya
Panda, Subhadarshi
Kotwal, Ketan
Dash, Amulya Ratna
Dash, Satya Ranjan
Sharma, Yashvardhan
Motlicek, Petr
Bojar, Ondrej
EXTERNAL
https://publications.idiap.ch/attachments/reports/2021/Parida_Idiap-RR-10-2021.pdf
PUBLIC
https://publications.idiap.ch/index.php/publications/showcite/Parida_WAT2021_2021
Related documents
Idiap-RR-10-2021
2021
Idiap
July 2021
This paper provides the description of shared tasks to the WAT 2021 by our team NLPHut's. We have participated in the English→Hindi Multimodal translation task, English→Malayalam Multimodal translation task, and Indic Multi-lingual 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 English→Malayalam Multimodal translation task (text-only translation, and Malayalam caption), and ranks second-best in English→Hindi Multimodal translation task (text-only translation, and Hindi caption). Our submissions have also performed well in the Indic Multilingual translation tasks.