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A language-vision model for translation

Author(s)
Fu, Allison.
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Download1192544690-MIT.pdf (2.687Mb)
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Boris Katz.
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MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
Machine translation or the automatic translation by computers from a source language to target language is a well-studied, difficult research problem. In recent years, there has been increased interest in grounding translation in vision. We introduce an unsupervised machine translation system grounded in video that can perform Chinese-English translation without the need for a parallel text corpus. In particular, we train separate Chinese and English generative language-vision models on only 267 captioned videos. We then perform translation by sampling video features for an input sentence in Chinese and finding the top-scoring English sentence or translation that describes the sampled video frames. We found that such a system picks out the correct translation with high accuracy and is a promising step towards augmenting language understanding with video.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020
 
Cataloged from the official PDF of thesis.
 
Includes bibliographical references (pages 55-58).
 
Date issued
2020
URI
https://hdl.handle.net/1721.1/127397
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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  • Electrical Engineering and Computer Sciences - Master's degree
  • Electrical Engineering and Computer Sciences - Master's degree

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