In One Hundred Words or Less

Abstract

This paper reports on research which aims to test the efficacy of applying automated evaluation techniques, originally designed for human second language learners, to machine translation (MT) system evaluation. We believe that such evaluation techniques will provide insight into MT evaluation, MT development, the human translation process and the human language learning process. The experiment described here looks only at the intelligibility of MT output. The evaluation technique is derived from a second language acquisition experiment that showed that assessors can differentiate native from non-native language essays in less than 100 words. Particularly illuminating for our purposes is the set of factor on which the assessors made their decisions. We duplicated this experiment to see if similar criteria could be elicited from duplicating the test using both human and machine translation outputs in the decision set. The encouraging results of this experiment, along with an analysis of language factors contributing to the successful outcomes, is presented here.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2001
Accession Number
AD1125330

Entities

People

  • Florence Reeder

Organizations

  • MITRE Corporation

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Accuracy
  • Acquisition
  • Dictionaries
  • Errors
  • Grammars
  • Intelligibility
  • Language
  • Learning
  • Linguistics
  • Machine Translation
  • Measurement
  • Natural Language Processing
  • Natural Languages
  • Ratings
  • Reliability
  • Spanish Language
  • Students
  • Test And Evaluation
  • Translations
  • Translators

Readers

  • Computational Linguistics
  • Speech Processing/Speech Recognition.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation