Secondly, the system calculates word-level scores based on the correct matched words using the determined correspondences of noun phrases.

The system calculates the final scores combining word-level scores and phrase-level scores.

2.2 Word-level Score

We report both word-level and letter-level error rates.

The word-level error rate is the fraction of words on which a method makes at least one mistake.

Specifically, for English our word-level accuracy (“ower”) is 96.33% while their best (“WA”) is 95.65%.

For both languages, PAT GEN has higher serious letter-level and word-level error rates than TEX using the existing pattern files.

The accuracy we achieve is slightly higher: word-level accuracy of 96.33% compared to their

Furthermore, the word-level alignments between Q and C can most often be identified with little ambiguity.

Thus we restrict our attention to those phrase transformations consistent with a good word-level alignment.

(2006) extend the error model by capturing word-level similarities learned from query logs.

In Section 2, we review the previous work on word-level confidence estimation which is used for error detection.

Ueffing and Ney (2007) exhaustively explore various word-level confidence measures to label each word in a generated translation hypothesis as correct or incorrect.

(2009) study several confidence features based on mutual information between words and n-gram and backward n-gram language model for word-level and sentence-level CE.