Phrase-level Quality Estimation for Machine Translation

By Varvara Logacheva, Lucia Specia. 2015

Subfields: Evaluation & Benchmarks, Machine Translation

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Evaluation & Benchmarks

1. Varvara Logacheva
2. Frédéric Blain
3. Lucia Specia
4. Carolina Scarton
5. Philipp Koehn
6. Ondrej Bojar
7. Matt Post
8. Kashif Shah

In Machine Translation

1. Frédéric Blain
2. Varvara Logacheva
3. Lucia Specia
4. Kashif Shah
5. Trevor Cohn
6. Daniel Beck

Citations in the corpus

• USFD’s Phrase-level Quality Estimation Systems (2016, methodology): “We chose to train a Conditional Random Fields (CRF) model because it has shown high performance in word-level QE (Luong et al., 2013) as well as phrase-level QE (Logacheva and Specia, 2015) Regularization of Weights (arow).”