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Towards a Brain-Machine System for Auditory Scene Analysis

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Wearable Electronics Sensors

Part of the book series: Smart Sensors, Measurement and Instrumentation ((SSMI,volume 15))

Abstract

In hearing aids, noise suppression algorithms that rely on spatial cues tend to improve the intelligibility of speech in noisy environments [1], [2], [3], [4]. Unfortunately, the location of target and noise sources can change rapidly in a natural, everyday acoustic environment. In fact, depending on what the listener is attending to, one source may be considered noise in one instant, and then considered the target in another instant. Adaptive filtering attempts to track the target source, but it is successful only under a set of simplifying constraints [5], [6]. It is much more effective to allow the user to determine the direction from which the target sound is coming.

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Author information

Authors and Affiliations

  1. Dartmouth College, Hanover, NH, USA

    Kofi Odame

  2. MC10 Inc., Cambridge, MA, USA

    Valerie Hanson

Authors
  1. Valerie Hanson
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  2. Kofi Odame
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Editors and Affiliations

  1. Massey University (Manawatu), Palmerston North, New Zealand

    Subhas C. Mukhopadhyay

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Hanson, V., Odame, K. (2015). Towards a Brain-Machine System for Auditory Scene Analysis. In: Mukhopadhyay, S. (eds) Wearable Electronics Sensors. Smart Sensors, Measurement and Instrumentation, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-319-18191-2_13

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  • DOI: https://doi.org/10.1007/978-3-319-18191-2_13

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18190-5

  • Online ISBN: 978-3-319-18191-2

  • eBook Packages: EngineeringEngineering (R0)

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