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Semantic spaces : behavior, language and word learning in the Human Speechome corpus

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dc.contributor.advisor Deb Roy. en_US
dc.contributor.author Miller, Matthew Adam en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Architecture. Program in Media Arts and Sciences. en_US
dc.date.accessioned 2012-03-16T16:04:40Z
dc.date.available 2012-03-16T16:04:40Z
dc.date.copyright 2011 en_US
dc.date.issued 2011 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/69805
dc.description Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2011. en_US
dc.description Cataloged from PDF version of thesis. en_US
dc.description Includes bibliographical references (p. 149-152). en_US
dc.description.abstract The Human Speechome Project is an unprecedented attempt to record, analyze and understand the process of language acquisition. It is composed of over 90,000 hours of video and 150,000 hours of audio, capturing roughly 80% of the waking hours of a single child from his birth until age 3. This thesis proposes and develops a method for representing and analyzing a video corpus of this scale that is both compact and efficient, while retaining much of the important information about large scale behaviors of the recorded subjects. This representation is shown to be useful for the unsupervised modeling, clustering and exploration of the data, particularly when it is combined with text transcripts of the speech. Novel methods are introduced to perform Spatial Latent Semantic Analysis - extending the popular framework for topic modeling to cover behavior as well. Finally, the representation is used to analyze the inherent "spatiality" of individual words. A surprising connection is demonstrated between the uniqueness of a word's spatial distribution and how early it is learned by the child. en_US
dc.description.statementofresponsibility by Matthew Miller. en_US
dc.format.extent 152 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Architecture. Program in Media Arts and Sciences. en_US
dc.title Semantic spaces : behavior, language and word learning in the Human Speechome corpus en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Architecture. Program in Media Arts and Sciences. en_US
dc.identifier.oclc 777966321 en_US


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