The AFRL-MITLL WMT16 News-Translation Task Systems

Abstract

This paper describes the AFRL-MITLL statistical machine translation systems and the improvements that were developed during the WMT16 evaluation campaign. As part of these efforts we have adapted a variety new techniques to our previous years systems including Neural Machine Translation, additional out-of-vocabulary transliteration techniques, and morphology generation.

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Document Details

Document Type
Technical Report
Publication Date
Aug 11, 2016
Accession Number
AD1032981

Entities

People

  • Brian J. Thompson
  • Elizabeth E. Salesky
  • Grant Erdmann
  • Jeremy Gwinnup
  • Katherine Young
  • Michaeel M. Kazi
  • Timothy Anderson

Organizations

  • MIT Lincoln Laboratory

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Coding
  • Computational Linguistics
  • Computational Science
  • Decoding
  • Errors
  • Information Processing
  • Information Systems
  • Language
  • Linguistics
  • Machine Translation
  • Natural Language Processing
  • Neural Networks
  • Recurrent Neural Networks
  • Test Sets
  • United States

Fields of Study

  • Computer science

Readers

  • Computational Linguistics

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation
  • AI & ML - Neural Networks