Name
Title | ||
|---|---|---|
An Investigation on the Effectiveness of Features for Translation Quality Estimation. |
Abstract | ||
|---|---|---|
We describe a systematic analysis on the effectiveness of features commonly exploited for the problem of predicting machine translation quality. Using a feature selection technique based on Gaussian Processes, we identify small subsets of features that perform well across many datasets for different language pairs, text domains, machine translation systems and quality labels. In addition, we show the potential of the reduced feature sets resulting from our feature selection technique to lead to significantly better performance in most datasets, as compared to the complete feature sets. |
Year | Venue | DocType |
|---|---|---|
2013 | MTSummit | Conference |
Volume | Citations | PageRank |
14 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kashif Shah | 1 | 103 | 11.69 |
| Trevor Cohn | 2 | 1649 | 110.69 |
| lucia specia | 3 | 1217 | 122.84 |