3 citations · 9 across the 3 of their papers we have counts for
8 papers
The Reality of Multi-Lingual Machine Translation
Tom Kocmi, Dominik Macháček, Ondřej Bojar
Our book "The Reality of Multi-Lingual Machine Translation" discusses the benefits and perils of using more than two languages in machine translation systems. While focused on the…
Lost in Interpreting: Speech Translation from Source or Interpreter?
Dominik Macháček, Matúš Žilinec, Ondřej Bojar
Interpreters facilitate multi-lingual meetings but the affordable set of languages is often smaller than what is needed. Automatic simultaneous speech translation can extend the se…
Presenting Simultaneous Translation in Limited Space
Dominik Macháček, Ondřej Bojar
Some methods of automatic simultaneous translation of a long-form speech allow revisions of outputs, trading accuracy for low latency. Deploying these systems for users faces the p…
Promoting the Knowledge of Source Syntax in Transformer NMT Is Not Needed
Thuong-Hai Pham, Dominik Macháček, Ondřej Bojar
The utility of linguistic annotation in neural machine translation seemed to had been established in past papers. The experiments were however limited to recurrent sequence-to-sequ…
A Speech Test Set of Practice Business Presentations with Additional Relevant Texts
Dominik Macháček, Jonáš Kratochvíl, Tereza Vojtěchová +1
We present a test corpus of audio recordings and transcriptions of presentations of students' enterprises together with their slides and web-pages. The corpus is intended for evalu…
English-Czech Systems in WMT19: Document-Level Transformer
Martin Popel, Dominik Macháček, Michal Auersperger +2
We describe our NMT systems submitted to the WMT19 shared task in English-Czech news translation. Our systems are based on the Transformer model implemented in either Tensor2Tensor…