Sangam: A Confluence of Knowledge Streams

Spoken command of large mobile robots in outdoor environments

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dc.contributor Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.contributor Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor Teller, Seth
dc.contributor Chuangsuwanich, Ekapol
dc.contributor Cyphers, David Scott
dc.contributor Glass, James R.
dc.contributor Teller, Seth
dc.creator Chuangsuwanich, Ekapol
dc.creator Cyphers, David Scott
dc.creator Glass, James R.
dc.creator Teller, Seth
dc.date 2011-05-19T22:28:04Z
dc.date 2011-05-19T22:28:04Z
dc.date 2010-12
dc.date.accessioned 2023-03-01T18:10:02Z
dc.date.available 2023-03-01T18:10:02Z
dc.identifier 978-1-4244-7902-3
dc.identifier 978-1-4244-7904-7
dc.identifier INSPEC Accession Number: 11774232
dc.identifier http://hdl.handle.net/1721.1/62852
dc.identifier Chuangsuwanich, E. et al. “Spoken command of large mobile robots in outdoor environments.” Spoken Language Technology Workshop (SLT), 2010 IEEE. 2010. 306-311. Copyright © 2010, IEEE
dc.identifier https://orcid.org/0000-0002-3097-360X
dc.identifier https://orcid.org/0000-0002-4896-8411
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/279002
dc.description We describe a speech system for commanding robots in human-occupied outdoor military supply depots. To operate in such environments, the robots must be as easy to interact with as are humans, i.e. they must reliably understand ordinary spoken instructions, such as orders to move supplies, as well as commands and warnings, spoken or shouted from distances of tens of meters. These design goals preclude close-talking microphones and “push-to-talk” buttons that are typically used to isolate commands from the sounds of vehicles, machinery and non-relevant speech. We used multiple microphones to provide omnidirectional coverage. A novel voice activity detector was developed to detect speech and select the appropriate microphone to listen to. Finally, we developed a recognizer model that could successfully recognize commands when heard amidst other speech within a noisy environment. When evaluated on speech data in the field, this system performed significantly better than a more computationally intensive baseline system, reducing the effective false alarm rate by a factor of 40, while maintaining the same level of precision.
dc.format application/pdf
dc.language en_US
dc.publisher Institute of Electrical and Electronics Engineers
dc.relation http://dx.doi.org/10.1109/SLT.2010.5700869
dc.relation IEEE Spoken Language Technology Workshop 2010
dc.rights Creative Commons Attribution-Noncommercial-Share Alike 3.0
dc.rights http://creativecommons.org/licenses/by-nc-sa/3.0/
dc.source MIT web domain
dc.title Spoken command of large mobile robots in outdoor environments
dc.type Article
dc.type http://purl.org/eprint/type/ConferencePaper


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