Multimodal speech interfaces for map-based applications

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-submi...

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Main Author: Liu, Sean (Sean Y.)
Other Authors: James R. Glass, Stephanie Seneff and Alexander Gruenstein.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2011
Subjects:
Online Access:http://hdl.handle.net/1721.1/61001
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spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-610012019-05-02T15:43:08Z Multimodal speech interfaces for map-based applications Liu, Sean (Sean Y.) James R. Glass, Stephanie Seneff and Alexander Gruenstein. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. 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. 2011-02-22T15:37:04Z 2011-02-22T15:37:04Z 2010 2010 Thesis http://hdl.handle.net/1721.1/61001 699525804 eng 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. http://dspace.mit.edu/handle/1721.1/7582 73 p. application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic Electrical Engineering and Computer Science.
spellingShingle Electrical Engineering and Computer Science.
Liu, Sean (Sean Y.)
Multimodal speech interfaces for map-based applications
description 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.
author2 James R. Glass, Stephanie Seneff and Alexander Gruenstein.
author_facet James R. Glass, Stephanie Seneff and Alexander Gruenstein.
Liu, Sean (Sean Y.)
author Liu, Sean (Sean Y.)
author_sort Liu, Sean (Sean Y.)
title Multimodal speech interfaces for map-based applications
title_short Multimodal speech interfaces for map-based applications
title_full Multimodal speech interfaces for map-based applications
title_fullStr Multimodal speech interfaces for map-based applications
title_full_unstemmed Multimodal speech interfaces for map-based applications
title_sort multimodal speech interfaces for map-based applications
publisher Massachusetts Institute of Technology
publishDate 2011
url http://hdl.handle.net/1721.1/61001
work_keys_str_mv AT liuseanseany multimodalspeechinterfacesformapbasedapplications
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