13 citations · 16 across the 6 of their papers we have counts for
6 papers
The eBible Corpus: Data and Model Benchmarks for Bible Translation for Low-Resource Languages
Vesa Akerman, David Baines, Damien Daspit +7
Efficiently and accurately translating a corpus into a low-resource language remains a challenge, regardless of the strategies employed, whether manual, automated, or a combination…
Adapting to the Low-Resource Double-Bind: Investigating Low-Compute Methods on Low-Resource African Languages
Colin Leong, Herumb Shandilya, Bonaventure F. P. Dossou +10
Many natural language processing (NLP) tasks make use of massively pre-trained language models, which are computationally expensive. However, access to high computational resources…
User Study for Improving Tools for Bible Translation
Joel Mathew, Ulf Hermjakob
Technology has increasingly become an integral part of the Bible translation process. Over time, both the translation process and relevant technology have evolved greatly. More rec…
Snow Mountain: Dataset of Audio Recordings of The Bible in Low Resource Languages
Kavitha Raju, Anjaly V, Ryan Lish +1
Automatic Speech Recognition (ASR) has increasing utility in the modern world. There are a many ASR models available for languages with large amounts of training data like English.…
Federated Named Entity Recognition
Joel Mathew, Dimitris Stripelis, José Luis Ambite
We present an analysis of the performance of Federated Learning in a paradigmatic natural-language processing task: Named-Entity Recognition (NER). For our evaluation, we use the l…
Biomedical Named Entity Recognition via Reference-Set Augmented Bootstrapping
Joel Mathew, Shobeir Fakhraei, José Luis Ambite
We present a weakly-supervised data augmentation approach to improve Named Entity Recognition (NER) in a challenging domain: extracting biomedical entities (e.g., proteins) from th…