13 citations · 20 across the 5 of their papers we have counts for
6 papers
Improving the quality of Web-mined Parallel Corpora of Low-Resource Languages using Debiasing Heuristics
Aloka Fernando, Nisansa de Silva, Menan Velyuthan +2
Parallel Data Curation (PDC) techniques aim to filter out noisy parallel sentences from web-mined corpora. Ranking sentence pairs using similarity scores on sentence embeddings der…
Linguistic Entity Masking to Improve Cross-Lingual Representation of Multilingual Language Models for Low-Resource Languages
Aloka Fernando, Surangika Ranathunga
Multilingual Pre-trained Language models (multiPLMs), trained on the Masked Language Modelling (MLM) objective are commonly being used for cross-lingual tasks such as bitext mining…
Shoulders of Giants: A Look at the Degree and Utility of Openness in NLP Research
Surangika Ranathunga, Nisansa de Silva, Dilith Jayakody +1
We analysed a sample of NLP research papers archived in ACL Anthology as an attempt to quantify the degree of openness and the benefit of such an open culture in the NLP community.…
Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora
Surangika Ranathunga, Nisansa de Silva, Menan Velayuthan +2
We conducted a detailed analysis on the quality of web-mined corpora for two low-resource languages (making three language pairs, English-Sinhala, English-Tamil and Sinhala-Tamil).…
Data Augmentation to Address Out-of-Vocabulary Problem in Low-Resource Sinhala-English Neural Machine Translation
Aloka Fernando, Surangika Ranathunga
Out-of-Vocabulary (OOV) is a problem for Neural Machine Translation (NMT). OOV refers to words with a low occurrence in the training data, or to those that are absent from the trai…
Data Augmentation and Terminology Integration for Domain-Specific Sinhala-English-Tamil Statistical Machine Translation
Aloka Fernando, Surangika Ranathunga, Gihan Dias
Out of vocabulary (OOV) is a problem in the context of Machine Translation (MT) in low-resourced languages. When source and/or target languages are morphologically rich, it becomes…