Work

Refinements to Interactive Translation Prediction Based on Search Graphs

Year: 2014

Type: conference-paper

Abstract: We propose a number of refinements to the canonical approach to interactive translation prediction.By more permissive matching criteria, placing emphasis on matching the last word of the user prefix, and dealing with predictions to partially typed words, we observe gains in both word prediction accuracy (+5.4%) and letter prediction accuracy (+9.3%).

Source: Proceedings of the conference - Association for Computational Linguistics. Meeting

DOI: 10.3115/v1/p14-2094

Authors: Philipp Koehn, Chara Tsoukala, Herve Saint-Amand

Institutions: Johns Hopkins University, University of Edinburgh

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: European Commission

Awards: G3207356259, G393177772, G5702163051, Cognitive Analysis and Statistical Methods for Advanced Computer Aided Translation