68 citations · 168 across the 11 of their papers we have counts for
20 papers · 1 filter
Pitfalls and Outlooks in Using COMET
Vilém Zouhar, Pinzhen Chen, Tsz Kin Lam +2
The COMET metric has blazed a trail in the machine translation community, given its strong correlation with human judgements of translation quality. Its success stems from being a…
EuroLLM: Multilingual Language Models for Europe
Pedro Henrique Martins, Patrick Fernandes, João Alves +12
The quality of open-weight LLMs has seen significant improvement, yet they remain predominantly focused on English. In this paper, we introduce the EuroLLM project, aimed at develo…
OpusCleaner and OpusTrainer, open source toolkits for training Machine Translation and Large language models
Nikolay Bogoychev, Jelmer van der Linde, Graeme Nail +7
Developing high quality machine translation systems is a labour intensive, challenging and confusing process for newcomers to the field. We present a pair of tools OpusCleaner and…
Don't Discard Fixed-Window Audio Segmentation in Speech-to-Text Translation
Chantal Amrhein, Barry Haddow
For real-life applications, it is crucial that end-to-end spoken language translation models perform well on continuous audio, without relying on human-supplied segmentation. For o…
Simultaneous Translation for Unsegmented Input: A Sliding Window Approach
Sukanta Sen, Ondřej Bojar, Barry Haddow
In the cascaded approach to spoken language translation (SLT), the ASR output is typically punctuated and segmented into sentences before being passed to MT, since the latter is ty…
Non-Autoregressive Machine Translation: It's Not as Fast as it Seems
Jindřich Helcl, Barry Haddow, Alexandra Birch
Efficient machine translation models are commercially important as they can increase inference speeds, and reduce costs and carbon emissions. Recently, there has been much interest…