activity
20182020
most citedMasakhane -- Machine Translation For Africa

24 citations · 65 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL2020★ 7 cited

Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages

Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila +45

Research in NLP lacks geographic diversity, and the question of how NLP can be scaled to low-resourced languages has not yet been adequately solved. "Low-resourced"-ness is a compl…

cs.LG2020★ 5 cited

A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning

Arnu Pretorius, Scott Cameron, Elan van Biljon +6

Multi-agent reinforcement learning has recently shown great promise as an approach to networked system control. Arguably, one of the most difficult and important tasks for which la…

cs.CL2020★ 20 cited

On Optimal Transformer Depth for Low-Resource Language Translation

Elan van Biljon, Arnu Pretorius, Julia Kreutzer

Transformers have shown great promise as an approach to Neural Machine Translation (NMT) for low-resource languages. However, at the same time, transformer models remain difficult…

cs.CL2020★ 24 cited

Masakhane -- Machine Translation For Africa

Iroro Orife, Julia Kreutzer, Blessing Sibanda +22

Africa has over 2000 languages. Despite this, African languages account for a small portion of available resources and publications in Natural Language Processing (NLP). This is du…

stat.ML2019

If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks

Arnu Pretorius, Elan van Biljon, Benjamin van Niekerk +6

Recent work in signal propagation theory has shown that dropout limits the depth to which information can propagate through a neural network. In this paper, we investigate the effe…

cs.CL2019

Unsupervised acoustic unit discovery for speech synthesis using discrete latent-variable neural networks

Ryan Eloff, André Nortje, Benjamin van Niekerk +7

For our submission to the ZeroSpeech 2019 challenge, we apply discrete latent-variable neural networks to unlabelled speech and use the discovered units for speech synthesis. Unsup…