4 citations · 5 across the 3 of their papers we have counts for
4 papers · 1 filter
Exploiting Domain-Specific Parallel Data on Multilingual Language Models for Low-resource Language Translation
Surangika Ranathungaa, Shravan Nayak, Shih-Ting Cindy Huang +6
Neural Machine Translation (NMT) systems built on multilingual sequence-to-sequence Language Models (msLMs) fail to deliver expected results when the amount of parallel data for a…
Leveraging Auxiliary Domain Parallel Data in Intermediate Task Fine-tuning for Low-resource Translation
Shravan Nayak, Surangika Ranathunga, Sarubi Thillainathan +6
NMT systems trained on Pre-trained Multilingual Sequence-Sequence (PMSS) models flounder when sufficient amounts of parallel data is not available for fine-tuning. This specificall…
Merkel Podcast Corpus: A Multimodal Dataset Compiled from 16 Years of Angela Merkel's Weekly Video Podcasts
Debjoy Saha, Shravan Nayak, Timo Baumann
We introduce the Merkel Podcast Corpus, an audio-visual-text corpus in German collected from 16 years of (almost) weekly Internet podcasts of former German chancellor Angela Merkel…
Pre-Trained Multilingual Sequence-to-Sequence Models: A Hope for Low-Resource Language Translation?
En-Shiun Annie Lee, Sarubi Thillainathan, Shravan Nayak +4
What can pre-trained multilingual sequence-to-sequence models like mBART contribute to translating low-resource languages? We conduct a thorough empirical experiment in 10 language…