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Found 14 papers, 3 papers with code
Consistent Human Evaluation of Machine Translation across Language Pairs
Obtaining meaningful quality scores for machine translation systems through human evaluation remains a challenge given the high variability between human evaluators, partly due to subjective expectations for translation quality for different language pairs.
How Robust is Neural Machine Translation to Language Imbalance in Multilingual Tokenizer Training?
Since a skewed data distribution is considered to be harmful, a sampling strategy is usually used to balance languages in the corpus.
Alternative Input Signals Ease Transfer in Multilingual Machine Translation
Further, we find that incorporating alternative inputs via self-ensemble can be particularly effective when training set is small, leading to +5 BLEU when only 5% of the total training data is accessible.
As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation
Mistranslated numbers have the potential to cause serious effects, such as financial loss or medical misinformation.
Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning
Neural machine translation systems are known to be vulnerable to adversarial test inputs, however, as we show in this paper, these systems are also vulnerable to training attacks.
The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation
One of the biggest challenges hindering progress in low-resource and multilingual machine translation is the lack of good evaluation benchmarks.
A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning
In this paper, we show that targeted attacks on black-box NMT systems are feasible, based on poisoning a small fraction of their parallel training data.
Pairwise Neural Machine Translation Evaluation
We present a novel framework for machine translation evaluation using neural networks in a pairwise setting, where the goal is to select the better translation from a pair of hypotheses, given the reference translation.
DiscoTK: Using Discourse Structure for Machine Translation Evaluation
We present novel automatic metrics for machine translation evaluation that use discourse structure and convolution kernels to compare the discourse tree of an automatic translation with that of the human reference.
CCAligned: A Massive Collection of Cross-Lingual Web-Document Pairs
We mine sixty-eight snapshots of the Common Crawl corpus and identify web document pairs that are translations of each other.
Egyptian Arabic to English Statistical Machine Translation System for NIST OpenMT'2015
The competition focused on informal dialectal Arabic, as used in SMS, chat, and speech.
The AMARA Corpus: Building Parallel Language Resources for the Educational Domain
This paper presents the AMARA corpus of on-line educational content: a new parallel corpus of educational video subtitles, multilingually aligned for 20 languages, i. e. 20 monolingual corpora and 190 parallel corpora.
