Search Results for author: Francisco Guzm{\'a}n

Found 17 papers, 1 papers with code

An Exploratory Study on Multilingual Quality Estimation

no code implementations Asian Chapter of the Association for Computational Linguistics 2020 Shuo Sun, Marina Fomicheva, Fr{\'e}d{\'e}ric Blain, Vishrav Chaudhary, Ahmed El-Kishky, Adithya Renduchintala, Francisco Guzm{\'a}n, Lucia Specia

Predicting the quality of machine translation has traditionally been addressed with language-specific models, under the assumption that the quality label distribution or linguistic features exhibit traits that are not shared across languages.

Machine Translation Translation

Are we Estimating or Guesstimating Translation Quality?

no code implementations ACL 2020 Shuo Sun, Francisco Guzm{\'a}n, Lucia Specia

Recent advances in pre-trained multilingual language models lead to state-of-the-art results on the task of quality estimation (QE) for machine translation.

Machine Translation Translation

Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions

no code implementations WS 2019 Philipp Koehn, Francisco Guzm{\'a}n, Vishrav Chaudhary, Juan Pino

Following the WMT 2018 Shared Task on Parallel Corpus Filtering, we posed the challenge of assigning sentence-level quality scores for very noisy corpora of sentence pairs crawled from the web, with the goal of sub-selecting 2{\%} and 10{\%} of the highest-quality data to be used to train machine translation systems.

Machine Translation Translation

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