Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6951452 | Computer Speech & Language | 2018 | 26 Pages |
Abstract
We find that common word unigrams and bigrams are the most salient features for translator fingerprinting across our two authors and four translators examined and are ultimately successful in our goal of classifying which text originated from a particular translator with accuracy measurements of over 90% on average.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Gerard Lynch, Carl Vogel,