Auditory Object Formation and Selection

  • Barbara Shinn-CunninghamEmail author
  • Virginia Best
  • Adrian K. C. Lee
Part of the Springer Handbook of Auditory Research book series (SHAR, volume 60)


Most normal-hearing listeners can understand a conversational partner in an everyday setting with an ease that is unmatched by any computational algorithm available today. This ability to reliably extract meaning from a sound source in a mixture of competing sources relies on the fact that natural, meaningful sounds have structure in both time and frequency. Such structure supports two processes that enable humans and animals to solve the cocktail party problem: auditory object formation and auditory object selection. These processes, which are closely intertwined and difficult to isolate, are linked to previous work on auditory scene analysis and auditory attention, respectively. This chapter considers how the brain may implement object formation and object selection. Specifically, the chapter focuses on how different regions of the brain cooperate to isolate the neural representation of sound coming from a source of interest and enhance it while suppressing the responses to distracting or unimportant sounds in a sound mixture.


Auditory grouping Auditory streaming Cocktail party Energetic masking Informational masking Scene analysis Selective attention 


Compliance with Ethics Requirements

Barbara Shinn-Cunningham has no conflicts of interest.

Virginia Best has no conflicts of interest.

Adrian K. C. Lee has no conflicts of interest.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Barbara Shinn-Cunningham
    • 1
    Email author
  • Virginia Best
    • 2
  • Adrian K. C. Lee
    • 3
  1. 1.Center for Research in Sensory Communication and Emerging Neural TechnologyBoston UniversityBostonUSA
  2. 2.Department of Speech, Language and Hearing SciencesBoston UniversityBostonUSA
  3. 3.Department of Speech and Hearing Sciences, Institute for Learning and Brain Sciences (I-LABS)University of WashingtonSeattleUSA

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