Speech Adaptation in Extended Ambient Intelligence Environments

Authors

  • Bonnie Dorr Institute for Human and Machine Cognition
  • Lucian Galescu Institute for Human and Machine Cognition
  • Ian Perera Institute for Human and Machine Cognition
  • Kristy Hollingshead-Seitz Institute for Human and Machine Cognition
  • David Atkinson Institute for Human and Machine Cognition
  • Micah Clark Institute for Human and Machine Cognition
  • William Clancey Institute for Human and Machine Cognition
  • Yorick Wilks Institute for Human and Machine Cognition
  • Eric Fosler-Lussier Ohio State University

DOI:

https://doi.org/10.1609/aaai.v29i1.9766

Keywords:

amyotrophic lateral sclerosis, automatic speech recognition, speech recognition, physiological degeneration, ambient intelligence, speech adaptation

Abstract

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 mass-produced, one-size-fits-all software currently in use on mobile devices.

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Published

2015-03-04

How to Cite

Dorr, B., Galescu, L., Perera, I., Hollingshead-Seitz, K., Atkinson, D., Clark, M., Clancey, W., Wilks, Y., & Fosler-Lussier, E. (2015). Speech Adaptation in Extended Ambient Intelligence Environments. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1). https://doi.org/10.1609/aaai.v29i1.9766