28 citations · 39 across the 6 of their papers we have counts for
7 papers · 1 filter
Neural Simultaneous Speech Translation Using Alignment-Based Chunking
Patrick Wilken, Tamer Alkhouli, Evgeny Matusov +1
In simultaneous machine translation, the objective is to determine when to produce a partial translation given a continuous stream of source words, with a trade-off between latency…
Novel Applications of Factored Neural Machine Translation
Patrick Wilken, Evgeny Matusov
In this work, we explore the usefulness of target factors in neural machine translation (NMT) beyond their original purpose of predicting word lemmas and their inflections, as prop…
Learning from Chunk-based Feedback in Neural Machine Translation
Pavel Petrushkov, Shahram Khadivi, Evgeny Matusov
We empirically investigate learning from partial feedback in neural machine translation (NMT), when partial feedback is collected by asking users to highlight a correct chunk of a…
Can Neural Machine Translation be Improved with User Feedback?
Julia Kreutzer, Shahram Khadivi, Evgeny Matusov +1
We present the first real-world application of methods for improving neural machine translation (NMT) with human reinforcement, based on explicit and implicit user feedback collect…
Neural Machine Translation Leveraging Phrase-based Models in a Hybrid Search
Leonard Dahlmann, Evgeny Matusov, Pavel Petrushkov +1
In this paper, we introduce a hybrid search for attention-based neural machine translation (NMT). A target phrase learned with statistical MT models extends a hypothesis in the NMT…
Neural and Statistical Methods for Leveraging Meta-information in Machine Translation
Shahram Khadivi, Patrick Wilken, Leonard Dahlmann +1
In this paper, we discuss different methods which use meta information and richer context that may accompany source language input to improve machine translation quality. We focus…