Expanding the language coverage of speech technology has the potential to improve
access to information for many more people. However, current speech technology is …

Driven by the goal of eradicating language barriers on a global scale, machine translation
has solidified itself as a key focus of artificial intelligence research today. However, such …

The development of neural techniques has opened up new avenues for research in
machine translation. Today, neural machine translation (NMT) systems can leverage highly …

This paper presents the results of the 2021 Shared Task on Open Machine Translation for
Indigenous Languages of the Americas. The shared task featured two independent tracks …

The performance of multilingual pretrained models is highly dependent on the availability of
monolingual or parallel text present in a target language. Thus, the majority of the world's …

Recent advances in the pre-training of language models leverage large-scale datasets to
create multilingual models. However, low-resource languages are mostly left out in these …

Pretrained multilingual models (PMMs) enable zero-shot learning via cross-lingual transfer,
performing best for languages seen during pretraining. While methods exist to improve …

In recent years machine translation has become very successful for high-resource language
pairs. This has also sparked new interest in research on the automatic translation of low …

Advancements in sign language processing have been hindered by a lack of sufficient data,
impeding progress in recognition, translation, and production tasks. The absence of …

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 …