activity
20172024
most citedNovel Applications of Factored Neural Machine Translation

9 citations · 16 across the 5 of their papers we have counts for

collaborators
Showing cs.CLShow all

6 papers · 1 filter

cs.CL20245 cited

Findings of the IWSLT 2024 Evaluation Campaign

Ibrahim Said Ahmad, Antonios Anastasopoulos, Ondřej Bojar +42

This paper reports on the shared tasks organized by the 21st IWSLT Conference. The shared tasks address 7 scientific challenges in spoken language translation: simultaneous and off…

cs.CL2022

AppTek's Submission to the IWSLT 2022 Isometric Spoken Language Translation Task

Patrick Wilken, Evgeny Matusov

To participate in the Isometric Spoken Language Translation Task of the IWSLT 2022 evaluation, constrained condition, AppTek developed neural Transformer-based systems for English-…

cs.CL20221 cited

SubER: A Metric for Automatic Evaluation of Subtitle Quality

Patrick Wilken, Panayota Georgakopoulou, Evgeny Matusov

This paper addresses the problem of evaluating the quality of automatically generated subtitles, which includes not only the quality of the machine-transcribed or translated speech…

cs.CL2020

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…

cs.CL20199 cited

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…

cs.CL20171 cited

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…