769 Machine Translation Papers Show Automatic Evaluation Worsening
Combing through papers released from 2010 to 2020, researchers identify overreliance on metric BLEU to the exclusion of 100+ alternatives — a major weak point. Continue reading
Tag: BLEU
New Machine Translation Metric Measures Correct and Consistent Term Use
Facebook, Naver, and George Mason University release open-sourced metric based on Covid-19 terms; hope to bridge gap between academia and industry. Continue reading
How to Improve Automatic Machine Translation Evaluation? Add Humans, Scientists Say
Scientists propose new system to standardize automatic evaluation of NLP systems by adding humans in the loop; encourage fellow researchers to submit text generation models for evaluation. Continue reading
Focusing on BLEU Can Bias Machine Translation Output
Though beam search can boost BLEU scores, it can also lead to high rates of misgendered pronouns, even when translating between two gendered languages. Continue reading
Here Are the Top 10 Most Influential Research Papers on Neural Machine Translation
The most-cited neural machine translation research papers show how NMT came to dominate the field — and how academia and industry’s interests have evolved. Continue reading
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Google Explores New Way to Improve Google Translate: Paraphrasing by Humans
Google study shows human-paraphrased reference translations and new evaluation metric, BLEUP, produce better translations. Findings to be integrated into consumer-facing products. Continue reading
Facebook Ramps Up Open Source Drive Into Speech Translation
Facebook AI invites developers to improve a speech translation dataset and a open sources a toolkit that evaluates simultaneous speech and text translation. Continue reading
And the Winner Is…ACL 2020 Announces Best Paper Awards
Association for Computational Linguistics names Best Research Papers of 2020 from a field of more than 3,000 submissions; paper that argues for retiring BLEU is runner-up. Continue reading
BLEU Has Measured Machine Translation Quality Since 2002. It’s Fast Becoming Useless.
As machine translation quality improves, precision-based metrics struggle to identify the best systems. Why have newer metrics not ousted longtime standard BLEU? Continue reading
A Quick Primer on Edit-Distance, a Key Metric in Post-Editing Machine Translation
As the language industry transitions to an operating model where the first draft is mostly generated by machines, many are looking for ways to quantify linguists' value-add. Edit-distance can help. Continue reading
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Researchers Propose New Way to Detect Machine Translation — Maybe Google Could Use It
Google has admitted machine translated content is a challenge to ranking algorithms. Researchers at the University of Tokyo may have found a solution: back-translation. Continue reading
NVIDIA Engineer on Machine Translation Research’s State-of-the Art and Future Direction
NVIDIA Senior Deep Learning Engineer Chip Huyen details progress on MT challenges, including data requirements, sentence-length limitations, and imperfect quality evaluation techniques. Continue reading
Facebook Patents Alternative to ‘Expensive’ BLEU
Facebook has been granted a patent for its machine translation quality evaluation system, which relies on user engagement data to decide which translation users prefer. Continue reading
As Neural Machine Translation’s Core Model Seems Settled, Focus Shifts to Products
At SlatorCon London 2019, Systran CEO Jean Senellart outlined the latest in NMT developments, called out some myths from vendors, and pointed out what’s missing from the industry. Continue reading
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