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cs.CL2018
On The Alignment Problem In Multi-Head Attention-Based Neural Machine Translation
Tamer Alkhouli, Gabriel Bretschner, Hermann Ney
This work investigates the alignment problem in state-of-the-art multi-head attention models based on the transformer architecture. We demonstrate that alignment extraction in tran…
cs.NE2018
RETURNN as a Generic Flexible Neural Toolkit with Application to Translation and Speech Recognition
Albert Zeyer, Tamer Alkhouli, Hermann Ney
We compare the fast training and decoding speed of RETURNN of attention models for translation, due to fast CUDA LSTM kernels, and a fast pure TensorFlow beam search decoder. We sh…