4 citations · 7 across the 4 of their papers we have counts for
4 papers
Efficient Sequence Training of Attention Models using Approximative Recombination
Nils-Philipp Wynands, Wilfried Michel, Jan Rosendahl +2
Sequence discriminative training is a great tool to improve the performance of an automatic speech recognition system. It does, however, necessitate a sum over all possible word se…
Towards Reinforcement Learning for Pivot-based Neural Machine Translation with Non-autoregressive Transformer
Evgeniia Tokarchuk, Jan Rosendahl, Weiyue Wang +4
Pivot-based neural machine translation (NMT) is commonly used in low-resource setups, especially for translation between non-English language pairs. It benefits from using high res…
Integrated Training for Sequence-to-Sequence Models Using Non-Autoregressive Transformer
Evgeniia Tokarchuk, Jan Rosendahl, Weiyue Wang +4
Complex natural language applications such as speech translation or pivot translation traditionally rely on cascaded models. However, cascaded models are known to be prone to error…
Learning Bilingual Sentence Embeddings via Autoencoding and Computing Similarities with a Multilayer Perceptron
Yunsu Kim, Hendrik Rosendahl, Nick Rossenbach +3
We propose a novel model architecture and training algorithm to learn bilingual sentence embeddings from a combination of parallel and monolingual data. Our method connects autoenc…