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Found 20 papers, 1 papers with code
Detection of Similar Languages and Dialects Using Deep Supervised Autoencoder
Language detection is considered a difficult task especially for similar languages, varieties, and dialects.
Silo NLP’s Participation at WAT2022
This paper provides the system description of “Silo NLP’s” submission to the Workshop on Asian Translation (WAT2022).
Overview of the 9th Workshop on Asian Translation
This paper presents the results of the shared tasks from the 9th workshop on Asian translation (WAT2022).
Overview of the 8th Workshop on Asian Translation
This paper presents the results of the shared tasks from the 8th workshop on Asian translation (WAT2021).
NLPHut’s Participation at WAT2021
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).
BertAA : BERT fine-tuning for Authorship Attribution
Identifying the author of a given text can be useful in historical literature, plagiarism detection, or police investigations.
Multimodal Neural Machine Translation System for English to Bengali
Multimodal Machine Translation (MMT) systems utilize additional information from other modalities beyond text to improve the quality of machine translation (MT).
Open Machine Translation for Low Resource South American Languages (AmericasNLP 2021 Shared Task Contribution)
This paper describes the team (“Tamalli”)’s submission to AmericasNLP2021 shared task on Open Machine Translation for low resource South American languages.
ODIANLP’s Participation in WAT2020
We have participated in the English-Hindi Multimodal task and Indic task.
Overview of the 7th Workshop on Asian Translation
This paper presents the results of the shared tasks from the 7th workshop on Asian translation (WAT2020).
Machine Translation by Projecting Text into the Same Phonetic-Orthographic Space Using a Common Encoding
One reason for this is the relative morphological richness of Indian languages, while another is that most of them fall into the extremely low resource or zero-shot categories.
Silo NLP's Participation at WAT2022
This paper provides the system description of "Silo NLP's" submission to the Workshop on Asian Translation (WAT2022).
Universal Dependency Treebank for Odia Language
This paper presents the first publicly available treebank of Odia, a morphologically rich low resource Indian language.
Hausa Visual Genome: A Dataset for Multi-Modal English to Hausa Machine Translation
The Hausa Visual Genome is the first dataset of its kind and can be used for Hausa-English machine translation, multi-modal research, and image description, among various other natural language processing and generation tasks.
OdiEnCorp 2.0: Odia-English Parallel Corpus for Machine Translation
The preparation of parallel corpora is a challenging task, particularly for languages that suffer from under-representation in the digital world.
Idiap NMT System for WAT 2019 Multimodal Translation Task
This paper describes the Idiap submission to WAT 2019 for the English-Hindi Multi-Modal Translation Task.
Abstract Text Summarization: A Low Resource Challenge
We propose an iterative data augmentation approach which uses synthetic data along with the real summarization data for the German language.
Overview of the 6th Workshop on Asian Translation
This paper presents the results of the shared tasks from the 6th workshop on Asian translation (WAT2019) including Ja↔En, Ja↔Zh scientific paper translation subtasks, Ja↔En, Ja↔Ko, Ja↔En patent translation subtasks, Hi↔En, My↔En, Km↔En, Ta↔En mixed domain subtasks and Ru↔Ja news commentary translation task.
Hindi Visual Genome: A Dataset for Multimodal English-to-Hindi Machine Translation
We present ``Hindi Visual Genome'', a multimodal dataset consisting of text and images suitable for English-Hindi multimodal machine translation task and multimodal research.
