no code implementations • IWSLT 2016 • Jan-Thorsten Peter, Andreas Guta, Nick Rossenbach, Miguel Graça, Hermann Ney
This work describes the statistical machine translation (SMT) systems of RWTH Aachen University developed for the evaluation campaign of International Workshop on Spoken Language Translation (IWSLT) 2016.
no code implementations • WS 2020 • Parnia Bahar, Patrick Wilken, Tamer Alkhouli, Andreas Guta, Pavel Golik, Evgeny Matusov, Christian Herold
AppTek and RWTH Aachen University team together to participate in the offline and simultaneous speech translation tracks of IWSLT 2020.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
no code implementations • WS 2016 • Yunsu Kim, Andreas Guta, Joern Wuebker, Hermann Ney
This work systematically analyzes the smoothing effect of vocabulary reduction for phrase translation models.