MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Understanding language through visual imagination

Author(s)
Mao, Cheahuychou.
Thumbnail
Download1145123680-MIT.pdf (3.938Mb)
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Boris Katz.
Terms of use
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
This thesis introduces a multimodal approach to natural language understanding by presenting a generative language-vision model that can generate videos for sentences and a comprehensive approach for using this capability to solve natural language inference, video captioning and video completion without task-specific training. The only training required is for acquiring a lexicon from captioned videos similar to the way children learn language through exposure to perceptual cues. The model generates videos by sampling the visual features of objects described in the target sentences over time. The evaluation results show that the model can reliably generate videos for sentences describing multiple concurrent and sequential actions, and that the ability to reason about language using visual scenes enables language tasks to be reduced to vision tasks and be solved more robustly using information obtained via vision.
Description
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
 
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
 
Cataloged from student-submitted PDF version of thesis.
 
Includes bibliographical references (pages 57-60).
 
Date issued
2019
URI
https://hdl.handle.net/1721.1/124257
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

Collections
  • Graduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.