2026-09-18T20:53:12Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/465252022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
James R. Glass.
Sun, Xin, M. Eng. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2009-08-26T16:42:18Z
2009-08-26T16:42:18Z
2008
2008
http://hdl.handle.net/1721.1/46525
413972628
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.
Includes bibliographical references (p. 75-76).
In recent years, much advancement has been made in both search and speech technology. The former seeks to organize and retrieve the ever-growing amount of online information efficiently, while the latter strives to increase mobility and accessibility in multimodal devices. Naturally, searching via spoken language will become ubiquitous in the near future. As a step towards realizing this goal, this thesis focuses on the simpler problem of bookmarking and retrieving websites via speech. With data collected from a user study, we gained insight on how to predict speech tags and query utterances based on a webpage's content. We then investigate and evaluate several heuristics for tagging and retrieving bookmarks with the objectives of maximizing recognition accuracy and retrieval rates. Finally, the progress culminates in a prototype Firefox extension that encapsulates an end-to-end system demonstrating speech integration into the bookmarking capabilities of the Firefox browser.
by Xin Sun.
M.Eng.
76 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
copyright. They may be viewed from this source for any purpose, but
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
A speech-enabled system for website bookmarking
Thesis
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