TY - GEN
T1 - Speech adaptation in Extended Ambient Intelligence environments
AU - Dorr, Bonnie J.
AU - Galescu, Lucian
AU - Perera, Ian
AU - Hollingshead-Seitz, Kristy
AU - Atkinson, David
AU - Clark, Micah
AU - Clancey, William
AU - Wilks, Yorick
AU - Fosler-Lussier, Eric
N1 - Publisher Copyright:
© Copyright 2015, Association for the Advancement of Artificial Intellegence. All rights reserved.
PY - 2015/6/1
Y1 - 2015/6/1
N2 - This Blue Sky presentation focuses on a major shift toward a notion of "ambient intelligence" that transcends general applications targeted at the general population. The focus is on highly personalized agents that accommodate individual differences and changes over time. This notion of Extended Ambient Intelligence (EAI) concerns adaptation to a person's preferences and experiences, as well as changing capabilities, most notably in an environment where conversational engagement is central. An important step in moving this research forward is the accommodation of different degrees of cognitive capability (including speech processing) that may vary over time for a given user-whether through improvement or through deterioration. We suggest that the application of divergence detection to speech patterns may enable adaptation to a speaker's increasing or decreasing level of speech impairment over time. Taking an adaptive approach toward technology development in this arena may be a first step toward empowering those with special needs so that they may live with a high quality of life. It also represents an important step toward a notion of ambient intelligence that is personalized beyond what can be achieved by massproduced, one-size-fits-all software currently in use on mobile devices.
AB - This Blue Sky presentation focuses on a major shift toward a notion of "ambient intelligence" that transcends general applications targeted at the general population. The focus is on highly personalized agents that accommodate individual differences and changes over time. This notion of Extended Ambient Intelligence (EAI) concerns adaptation to a person's preferences and experiences, as well as changing capabilities, most notably in an environment where conversational engagement is central. An important step in moving this research forward is the accommodation of different degrees of cognitive capability (including speech processing) that may vary over time for a given user-whether through improvement or through deterioration. We suggest that the application of divergence detection to speech patterns may enable adaptation to a speaker's increasing or decreasing level of speech impairment over time. Taking an adaptive approach toward technology development in this arena may be a first step toward empowering those with special needs so that they may live with a high quality of life. It also represents an important step toward a notion of ambient intelligence that is personalized beyond what can be achieved by massproduced, one-size-fits-all software currently in use on mobile devices.
UR - http://www.scopus.com/inward/record.url?scp=84961207154&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84961207154&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84961207154
T3 - Proceedings of the National Conference on Artificial Intelligence
SP - 4027
EP - 4031
BT - Proceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015
PB - AI Access Foundation
T2 - 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015
Y2 - 25 January 2015 through 30 January 2015
ER -