4 papers
Improving Unsupervised Word-by-Word Translation with Language Model and Denoising Autoencoder
Yunsu Kim, Jiahui Geng, Hermann Ney
Unsupervised learning of cross-lingual word embedding offers elegant matching of words across languages, but has fundamental limitations in translating sentences. In this paper, we…
Unsupervised Training for Large Vocabulary Translation Using Sparse Lexicon and Word Classes
Yunsu Kim, Julian Schamper, Hermann Ney
We address for the first time unsupervised training for a translation task with hundreds of thousands of vocabulary words. We scale up the expectation-maximization (EM) algorithm t…
A Comparative Study on Vocabulary Reduction for Phrase Table Smoothing
Yunsu Kim, Andreas Guta, Joern Wuebker +1
This work systematically analyzes the smoothing effect of vocabulary reduction for phrase translation models. We extensively compare various word-level vocabularies to show that th…
RETURNN: The RWTH Extensible Training framework for Universal Recurrent Neural Networks
Patrick Doetsch, Albert Zeyer, Paul Voigtlaender +3
In this work we release our extensible and easily configurable neural network training software. It provides a rich set of functional layers with a particular focus on efficient tr…