2026-09-19T17:52:49Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/610012022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
James R. Glass, Stephanie Seneff and Alexander Gruenstein.
Liu, Sean (Sean Y.)
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2011-02-22T15:37:04Z
2011-02-22T15:37:04Z
2010
2010
http://hdl.handle.net/1721.1/61001
699525804
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 71-73).
This thesis presents the development of multimodal speech interfaces for mobile and vehicle systems. Multimodal interfaces have been shown to increase input efficiency in comparison with their purely speech or text-based counterparts. To date, much of the existing work has focused on desktop or large tablet-sized devices. The advent of the smartphone and its ability to handle both speech and touch inputs in combination with a screen display has created a compelling opportunity for deploying multimodal systems on smaller-sized devices. We introduce a multimodal user interface designed for mobile and vehicle devices, and system enhancements for a dynamically expandable point-of-interest database. The mobile system is evaluated using Amazon Mechanical Turk and the vehicle- based system is analyzed through in-lab usability studies. Our experiments show encouraging results for multimodal speech adoption.
by Sean Liu.
M.Eng.
73 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.
Multimodal speech interfaces for map-based applications
Thesis
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Publication
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<Abstract>This thesis presents the development of multimodal speech interfaces for mobile and vehicle systems. Multimodal interfaces have been shown to increase input efficiency in comparison with their purely speech or text-based counterparts. To date, much of the existing work has focused on desktop or large tablet-sized devices. The advent of the smartphone and its ability to handle both speech and touch inputs in combination with a screen display has created a compelling opportunity for deploying multimodal systems on smaller-sized devices. We introduce a multimodal user interface designed for mobile and vehicle devices, and system enhancements for a dynamically expandable point-of-interest database. The mobile system is evaluated using Amazon Mechanical Turk and the vehicle- based system is analyzed through in-lab usability studies. Our experiments show encouraging results for multimodal speech adoption.</Abstract>
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