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Massachusetts Institute of Technology

A framework for multi-modal input in a pervasive computing environment

Abstract

dc:description.abstract

In this thesis, we propose a framework that uses multiple-domains and multi-modal techniques to disambiguate a variety of natural human input modes. This system is based on the input needs of pervasive computing users. The work extends the Galaxy architecture developed by the Spoken Language Systems group at MIT. Just as speech recognition disambiguates an input wave form by using a grammar to find the best matching phrase, we use the same mechanism to disambiguate other input forms, T9 in particular. A skeleton version of the framework was implemented to show this framework is possible and to explore some of the issues that might arise. The system currently works for both T9 and Speech modes. The framework also includes potential for any other type of input for which a recognizer can be built such as graffiti input.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2002

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Agarwal, Shalini, 1979-
Advisor dc:contributor.advisor
  • Larry Rudolph.

Subjects

dc:subject × 1

Rights

dc:rights
Statement 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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/16825
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/16825

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Agarwal, Shalini, 1979-. A framework for multi-modal input in a pervasive computing environment. Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/16825