The IWSLT 2016 evaluation campaign
Abstract The IWSLT 2016 Evaluation Campaign featured two tasks: the translation of talks
and the translation of video conference conversations. While the first task extends previously …
and the translation of video conference conversations. While the first task extends previously …
Stronger baselines for trustable results in neural machine translation
Interest in neural machine translation has grown rapidly as its effectiveness has been
demonstrated across language and data scenarios. New research regularly introduces …
demonstrated across language and data scenarios. New research regularly introduces …
Neural versus phrase-based mt quality: An in-depth analysis on english–german and english–french
Within the field of statistical machine translation, the neural approach (NMT) is currently
pushing ahead the state of the art performance traditionally achieved by phrase-based …
pushing ahead the state of the art performance traditionally achieved by phrase-based …
Detecting cross-lingual semantic divergence for neural machine translation
Parallel corpora are often not as parallel as one might assume: non-literal translations and
noisy translations abound, even in curated corpora routinely used for training and …
noisy translations abound, even in curated corpora routinely used for training and …
Metric score landscape challenge (MSLC23): Understanding metrics' performance on a wider landscape of translation quality
Abstract The Metric Score Landscape Challenge (MSLC23) dataset aims to gain insight into
metric scores on a broader/wider landscape of machine translation (MT) quality. It provides a …
metric scores on a broader/wider landscape of machine translation (MT) quality. It provides a …
Identifying semantic divergences in parallel text without annotations
Recognizing that even correct translations are not always semantically equivalent, we
automatically detect meaning divergences in parallel sentence pairs with a deep neural …
automatically detect meaning divergences in parallel sentence pairs with a deep neural …
Robust neural machine translation for clean and noisy speech transcripts
Neural machine translation models have shown to achieve high quality when trained and
fed with well structured and punctuated input texts. Unfortunately, the latter condition is not …
fed with well structured and punctuated input texts. Unfortunately, the latter condition is not …
[PDF][PDF] Multi-source Neural Automatic Post-Editing: FBK's participation in the WMT 2017 APE shared task
Previous phrase-based approaches to Automatic Post-editing (APE) have shown that the
dependency of MT errors from the source sentence can be exploited by jointly learning from …
dependency of MT errors from the source sentence can be exploited by jointly learning from …
[PDF][PDF] Empirical investigation of optimization algorithms in neural machine translation
Training neural networks is a non-convex and a high-dimensional optimization problem. In
this paper, we provide a comparative study of the most popular stochastic optimization …
this paper, we provide a comparative study of the most popular stochastic optimization …
Assessing the tolerance of neural machine translation systems against speech recognition errors
Machine translation systems are conventionally trained on textual resources that do not
model phenomena that occur in spoken language. While the evaluation of neural machine …
model phenomena that occur in spoken language. While the evaluation of neural machine …